List of Papers
- • [ADSMI2024] Physics-informed Unsupervised Test-time Adaptation for MRI Super-Resolution
- • [ADSMI2024] Variational multimodal distillation for diagnosing plaque vulnerability in carotid 3D MRI
- • [ADSMI2024] MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions
- • [ADSMI2024] CoMoTo: Unpaired Cross-Modal Lesion Distillation Improves Breast Lesion Detection in Tomosynthesis
- • [ADSMI2024] Learning from Similarity Proportion Loss for Classifying Skeletal Muscle Recovery Stages
- • [ADSMI2024] LoGex: Improved tail detection of extremely rare histopathology classes via guided diffusion
- • [ADSMI2024] SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation
- • [ADSMI2024] Unsupervised Domain Adaptation for Pediatric Brain Tumor Segmentation
- • [ADSMI2024] Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods
- • [ADSMI2024] Federated Self-supervised Domain Generalization for Label-efficient Polyp Segmentation
- • [ADSMI2024] Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representations
- • [ADSMI2024] AMAES: Augmented Masked Autoencoder Pretraining on Public Brain MRI Data for 3D-Native Segmentation
- • [ADSMI2024] Enhancing Single-Slice Segmentation with 3D-to-2D Unpaired Scan Distillation
- • [ADSMI2024] Enhancing the automatic segmentation and analysis of 3D liver vasculature models
- • [ADSMI2024] Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning
- • [ADSMI2024] The Effect of Lossy Compression on 3D Medical Images Segmentation with Deep Learning
- • [ADSMI2024] DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology Diagnosis
- • [AFRICAI] NaijaCXR-VLM: A Multi-task Vision-Language Model for Chest X-ray Analysis in Low-resource Settings
- • [AFRICAI] CT X-ray Tube RUL Estimation Under Data Scarcity in Low-Resource Hospitals
- • [AFRICAI] Do Medical Foundation Models Generalize on the African Brain?
- • [AFRICAI] Towards Privacy-Preserving Multi-Site ICH Detection for South African Telestroke Networks
- • [AFRICAI] Afro-FetalNet: Fetal Plane Classification for Low-Resource African Settings
- • [AFRICAI] From Manuals to Maintenance: Fine-Tuning MedGemma for Multi-Modal Imaging System Support in Low-Resource Settings
- • [AFRICAI] From Disorder to Volume: Transformer-Based 3D MRI Reconstruction from Unstructured JPEG Archives
- • [AFRICAI] ULF-Synth: Physics-Guided Ultra-Low-Field MRI Enhancement for Pediatric Neuroimaging
- • [AFRICAI] Harmful or Helpful? When Precision-Recall Balance Governs Safe QGFL Transfer in Malaria Detection
- • [AFRICAI] Infrastructure Readiness Assessment for Federated Learning in Medical Imaging across African Sites
- • [AFRICAI] Improving Feature Representations for Few-shot Classification of Neglected Tropical Diseases on Dark Skin Tones
- • [AFRICAI] Resource-Efficient Knowledge Distillation via Simulated Annealing for Lightweight Breast Cancer Detection
- • [AFRICAI] MoonScan: An AI-Based Clinical Decision-Support System for Chest X-Ray Analysis in a Low-Resource African Setting
- • [AFRICAI] Domain Shift in Prostate MRI AI: Proxy Validation on a Low-Resource 1.5T Clinical Cohort
- • [AFRICAI] LRX-Bench: Robustness Evaluation of an RLVR-Trained Medical Vision–Language Model under Deployment-Motivated Chest X-ray Degradations
- • [AFRICAI] A Modality-Invariant and Fair Representation Framework for Skin Disease Classification
- • [AFRICAI] Beyond External Validation: Evaluating the Deployment Readiness of Medical Imaging AI in an African Clinical Context through Diabetic Retinopathy Screening
- • [AFRICAI] Preprocessing as Prior: Rethinking Self-Supervised Representation Learning in Cardiac Sound Classification
- • [AFRICAI] Federated Learning under Combined Clinical Heterogeneity: Evaluation Protocol and Inter-Site Equity
- • [AFRICAI] Accurate but Not Equally Trustworthy: Benchmarking Foundation Models for Fetal Ultrasound in Africa
- • [AFRICAI] Evaluating the Generalization of Neuroimaging Foundation Models on African Brain MRI
- • [AFRICAI] PREPARED OR UNPREPARED? EVALUATING HEALTHCARE WORKFORCE READINESS FOR CLINICAL ADOPTION OF ARTIFICIAL INTELLIGENCE IN NIGERIA
- • [AFRICAI] Benchmarking Foundation Models for Cervical Cancer CT Reporting in Zambia
- • [AFRICAI] Self-supervised Learning Versus Segmentation-aware Augmentation for Acute Ischemic Stroke CT Segmentation Under Annotation Scarcity
- • [AFRICAI] Annotation-Efficient Conditional Diffusion for Subacute Stroke Segmentation in West African Non-Contrast CT: A Calibration-First Evaluation
- • [AIIG2024] Counterfactual analysis of genotype variant effects on imaging-derived phenotypes
- • [AIIG2024] Multimodal Analysis of White Blood Cell Differentiation in Acute Myeloid Leukemia Patients using a β-Variational Autoencoder
- • [AIMS-TBI] Shared nnU-Net Probability Maps for msTBI Lesion Detection and Segmentation
- • [AIMS-TBI] Diagnosing the Recall Tail: A Class-Imbalance Study of nnU-Net for Detection and Segmentation of Heterogeneous Moderate–Severe TBI Lesions
- • [AIMS-TBI] ATVNet: Adaptive Transformer-Enhanced V-Net for Automated msTBI Lesion Segmentation
- • [AIMS-TBI] Rebalancing Lesion Exposure: Instance-Aware Sampling for msTBI Lesion Segmentation
- • [AIMS-TBI] Task-Specific MedNeXt and Heterogeneous Ensembling for Traumatic Brain Injury Lesion Analysis on T1-Weighted MRI
- • [AIMS-TBI] Dual-Model nnU-Net Strategy for TBI Segmentation and Detection in T1-weighted MRI
- • [AIMS-TBI] Hybrid Ensemble with Multi-Patch Fine-Tuning for Traumatic Brain Injury Segmentation
- • [AIMS-TBI] nnU-Net and Domain Randomization for Automated Segmentation of Moderate-to-Severe Traumatic Brain Injury
- • [AIMS-TBI] Evaluating Large-Scale Pretraining and Auxiliary Training Data for T1-only TBI Lesion Detection and Segmentation in the AIMS-TBI 2026 Challenge
- • [AIMS-TBI] A U-Net for Automated msTBI Lesion Segmentation
- • [AIMS-TBI] Single-Model Lesion Detection and Segmentation for Moderate–Severe Traumatic Brain Injury on T1-weighted MRI
- • [AIMS-TBI] Task-Specific T1 MRI Pipelines for TBI: Knowledge-Distilled Segmentation and ICV-Cascaded Detection
- • [AMAI] Segmentation-Guided Multiple Instance Learning for Cardiac MRI Disease Classification
- • [AMAI] Pre-Deployment Stress Testing of Source-Grounded Conversational AI in Non-Imaging Mental-Health Contexts: A 100-Query, 20-Risk-Category Methodology with Grounded-Refusal Contracts
- • [AMAI] Assessing the clinical readiness of SAM2 for CT-based tibial implant displacement quantification
- • [AMAI] Longitudinal 3D Foundation Modeling for Neoadjuvant Breast Cancer Response Prediction from Serial DCE-MRI
- • [AMAI] On-Device Multi-Species Malaria Detection with Uncertainty-Calibrated Slide-Level Aggregation
- • [AMAI] ArdsTracker: Time-series physiological neural networks for predicting respiratory failure based on chest X-ray
- • [AMAI] Population-Scale Segmentation of Penile Tissue in Dixon MRI using Deep Learning for Quantitative Phenotyping in Male Reproductive Health
- • [AMAI] SonoAudit: A Framework for Auditing Caliper Placement in Fetal Ultrasound Biometry
- • [AMAI] Appendicular Lean Mass Estimation from Dual-View DXA Scans Using Hierarchical Fusion
- • [AMAI] VAMP-PD: A Task-Structured Single-Camera Video Benchmark for MDS-UPDRS Motor Severity Assessment in Parkinson’s Disease
- • [AMAI] Determinism, Plausibility, and Clinical Trust in CT-to-MRI Translation for Emergency Spine Imaging
- • [AMAI] Modeling Abnormality as Semantic Deviation for Few-Shot Medical Anomaly Detection
- • [AMAI] What Does an AI Model Learn About Stress? A SHAP-Based Behavioural Interpretation of a Wearable Stress Classifier
- • [AMAI] Mesenteric Arterial Vessel Segmentation in Abdominal CT with Small Bowel Obstruction
- • [AMAI] BARW-GP: Workload-Aware Threshold Selection for Multi-Label Medical AI Alerting Across Chest X-ray and ECG
- • [AMAI] Towards Practical Algorithm Selection for Unsupervised Domain Adaptation in Medical Imaging
- • [AMAI] NeurGait: A Vision-Language Framework for Structured Gait Assessment Support in Parkinson’s Disease and Multiple Sclerosis
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• [AMAI] EuropeMedQA: A Multilingual, Multimodal Medical Examination Dataset for Language Model Evaluation
- Causio, Francesco Andrea; Riccomi, Olivia; De Vita, Vittorio; Felizzi, Federico; Ferramola, Michele; Tosi, Alessandro; Cristiano, Antonio; De Mori, Lorenzo; Battipaglia, Chiara; Sawaya, Melissa; De Angelis, Luigi; Di Pumpo, Marcello; Piscitelli, Alessandra; Risuleo, Pietro Eric; Longo, Alessia; Vojvodic, Giulia; Vassalli, Mariapia; Castaniti, Bianca Destro; Scarsi, Nicolò; Del Medico, Manuel;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [AMAI] Learning Diagnostic Reasoning for Decision Support in Toxicology
- • [AMAI] Adaptive Riemannian Geometry for Seizure Onset Zone Localization in Intracranial Electroencephalography
- • [AMAI] Dual-Encoder Transfer Learning for Surgical Image Segmentation
- • [AMAI] Stratified Iterative Learning for Kidney Cortex and Medulla Segmentation Across Healthy and Pathological Kidneys on Contrast-Enhanced CT
- • [AMAI] Explainable and Uncertainty-Aware Chest X-ray Classification with Selective Referral
- • [AMAI] Continual Learning with subspace adaptation in foundation models for drug safety studies
- • [AMAI] Predicting Clinically Actionable LUAD Mutations from Whole-Slide Histopathology Using Prov-GigaPath Foundation Model Embeddings
- • [AMAI] Weakly Supervised Instance-Level Gleason Pattern Estimation Using Primary and Secondary Labels
- • [AMAI] Prediction of Atrial Fibrillation Onset from Continuous Intensive Care Unit ECG Monitoring: A Deep Learning Approach
- • [AMAI] Association of Cardiovascular Risk Factors with Segmentation-Free Motion-Derived Coronary Artery Dynamics
- • [AMAI] A Benchmark Audit of Site Confounds, Calibration, and Self-Supervision in Cross-Dataset Parkinson’s EEG Detection
- • [AMAI] Beyond Explanation: Debugging Medical Imaging Models via Concept Intervention
- • [AMPLIFAI] Ordinal-aware Multi-Phase Classification with Manifold Mixup for LI-RADS Assessment in CT
- • [AMPLIFAI] Read to Decide: Interpretable Feature-Guided LI-RADS Categorization from Multiphase CT
- • [AMPLIFAI] Metric-Aligned Cross-Phase Attention for LI-RADS Categorization of Liver Lesions on Multi-Phase CT
- • [AMPLIFAI] Shortcut-Aware Validation for LI-RADS Categorisation on Multi-Phase CT
- • [AMPLIFAI] Multi-Source Feature Fusion for LI-RADS Classification in Multi-Phase CT
- • [AMPLIFAI] PHORA: Physiology-Guided Hierarchical Ordinal Radiomics for LI-RADS Classification in Multiphase CT
- • [AMPLIFAI] Clinically-grounded Multiphasic Modeling for Interpretable LI-RADS Categorization
- • [AMPLIFAI] Dual-Scale Phase-Aware 3D ViT with Bounded Tubular Rescue for LI-RADS Classification
- • [ASMUS] EchoAFR: Echocardiography Multi-video Report Generation Through Anatomical and Functional Aware Hierarchical Q-former
- • [ASMUS] EchoFAM: Frequency Prior-Driven Adaptation of SAM2 for Echocardiography Video Segmentation
- • [ASMUS] Controllable Synthesis of Pathological Fetal Brain Ultrasound via Registration-Guided, Radiomics-Driven Latent Diffusion
- • [ASMUS] UltraPIPS: Improving model perception in B-mode ultrasound with foundation models
- • [ASMUS] Echo-E3Net: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation
- • [ASMUS] Speckle-Aware Signal Extraction as an Alternative to Complex Methods for ECG-Free Cardiac Phase Detection
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• [ASMUS] Recurrent Contrastive Learning for Imbalanced Medical Image Classification
- Zhu, Zhiyuan; Meng, Xinling; Yu, Junxuan; Chen, Jiongquan; Ni, Qiongying; Shao, Tuhang; Huang, Yuhao; Zhou, Luping; Huang, Ruiyang; Wang, Yuxue; Zhang, Rongliang; Wang, Xue; Tang, Tianhong; Wang, Likun; Chen, Junbo; Jiang, Yong; Lu, Yongping; Yang, Xin;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [ASMUS] ProME-Net: Prototype-Guided Artifact-Robust Breast Ultrasound Video Detection
- • [ASMUS] From Oracle Boxes to Automatic Prompts: Benchmarking Frontier Foundation Models for Thyroid Ultrasound Segmentation
- • [ASMUS] Learning to Annotate, Optimizing to Estimate: A De-amortized Inference Framework for Ultrasound Confidence Maps
- • [ASMUS] USPose: Improving 3D Fetal Brain Plane Localization for Volumetric Reconstruction from 2D Ultrasound with SO(3)-Equivariance
- • [ASMUS] BUThink: Aligning Multiparametric Breast Ultrasound with Clinical Expert Logic via Rule-Constrained GRPO
- • [ASMUS] Self-Supervised Cardiac Phase Detection via Single-Parameter Latent Orbits
- • [ASMUS] Multivariate Gaussian NeRF for Wide Field-of-View Ultrasound Reconstruction
- • [ASMUS] An Eye Tracking Study on the Ultrasound Inspection Strategies of Expert and Novice Sonographers
- • [ASMUS] Beyond Per-Frame Accuracy: Temporally Consistent Carotid Strain Tracks Cardiovascular Risk
- • [ASMUS] UltraBend: Refraction-Aware Propagation Modeling for Speed of Sound Imaging in Ultrasound
- • [ASMUS] Assessing Spatio-temporal Foundation Models for Clinical Mitral Regurgitation Grading
- • [ASMUS] TargetIQA: Anatomy-Aware Ultrasound Image Quality Assessment
- • [ASMUS] From Pretraining to Clinical Tasks: Transfer of Foundation Models in Ultrasound Multi-Task Learning
- • [ASMUS] Deformable CT-US Registration via Anatomy-Aware Implicit Neural Representations
- • [ASMUS] CATCH: Cross-View Attention for Consistent Multi-Chamber Heart Segmentation
- • [ASMUS] ALRAU: Atlas Learning from Routine Antenatal Ultrasound
- • [ASMUS] Medical Image Registration Metrics Examined for TRUS-Guided Prostate Interventions
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• [ASMUS] Global to Local Registration: Transferring Pretrained Registration Models to CT/MR–Ultrasound via Anatomical Supervision
- d’Albenzio, Gabriella; Liu, Mengting; Ma, Shixing; Yang, Chunna; Wei, Yuhao; Vasu, Shrisharanyan; Vijesh, Aniketh; Ma, Xihan; Taylor, Zachary P.; Pias, Tanmoy Sarkar; Demir, Başar; Gyöngy, Miklós; Ceran, Yasin; Niethammer, Marc; Kapur, Tina; Aylward, Stephen; Fichtinger, Gabor; Min, Zhe; Rusu, Mirabela;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [ASMUS] Automated Micro-Ultrasound Prostate Volume for MRI-Free PSA-Density: Reproducibility and Agreement with MRI
- • [ASMUS] Beyond Single Diagnostic Accuracy: Three-Level Hierarchical Evaluation of Accuracy and Reliability in Multimodal LLM for Ultrasound Interpretation
- • [BraTS-GoAT] Multi-Stage Prompt-Guided Feature Modulation for Generalizable Brain Tumor Segmentation
- • [BraTS-GoAT] SlimInterPAS for Brain Tumor Segmentation
- • [BraTS-GoAT] An Engineering-optimized, Resource-Constrained nnU-Net v2 Pediatric Baseline for the BraTS-GoAT 2026 Generalizability-Across-Tumors Challenge
- • [BraTS-GoAT] MISFIT: A Self-Supervised Pretraining Toolkit for 3D Medical Imaging — A Preliminary Test Across Three BraTS 2026 Segmentation Tasks
- • [BraTS-GoAT] MCS-UNet: A Multimodal Collaborative Framework for Robust Multi-center MRI Brain Tumor Segmentation
- • [BraTS-GoAT] RACER: A Radiomic-Adaptive Cohort Ensemble with Refinement for Cross-cohort Brain Tumor Segmentation using Deep Learning
- • [BraTS-GoAT] Pseudo-Label Enhanced SpikeFormer-UNet for Generalizable Brain Tumor Segmentation
- • [BraTS-GoAT] Generalizable Brain Tumor Segmentation with Self-Training and Tumor-Aware Deformations
- • [BraTS-GoAT] Self-Supervised Pretraining for Generalizable Brain Tumor Segmentation in the BraTS-GoAT Challenge
- • [BraTS-GoAT] Assessing nnU-Net Generalization across Brain Tumor Populations in BraTS-GoAT 2026
- • [BraTS-GoAT] Generalizable Brain Tumor Sub-Region Segmentation Across Tumor Entities via Recall-Oriented Pseudo-Labeling and Modality-Dropout Dual-View Ensembling
- • [BraTS-GoAT] A Systematic Evaluation of Learning Strategies for Generalizable Brain Tumor Segmentation Across Heterogeneous Tumor Populations
- • [BraTS-GoAT] Reliability analysis for BraTS-GoAT segmentation: a controlled robustness study of deep-ensemble uncertainty
- • [BraTS-GoAT] A Self-Configuring Model versus Fused Ensembles for Brain Tumor Segmentation on the BraTS-GoAT Benchmark
- • [BraTS-GoAT] Generalisation Across Tumor Entities with a From-Scratch Residual-Encoder U-Net: A Baseline and an Analysis of Training–Validation Distribution Shift
- • [BraTS-GoAT] AIstatLab at BraTS-GoAT 2026 Task 3: Quality-Controlled Consensus Pseudo-Labeling and Dense Expert Adaptation
- • [BraTS-GoAT] Regions7525_DA5: Harnessing Adaptations of Existing nnU-Net Features to Improve Generalizability of Brain Tumor Segmentation
- • [BraTS-GoAT] GAT-26: Release-Path Auditing and Confirmation-Gated Inference Selection for Cross-Tumor Brain Tumor Segmentation
- • [BraTS-Inpainting] Enhanced 3D U-Net for BraTS Local Synthesis: Attention, Deep Supervision, and Edge-Aware Inpainting
- • [BraTS-Inpainting] Zero-Shot Brain MRI Inpainting with 2.5D Unconditional Flow Priors
- • [BraTS-Inpainting] Conditional Flow Matching for Local Synthesis of Healthy Brain Tissue in 3D MRI
- • [BraTS-Inpainting] Dynamic Shape-Aware Mask-Augmented Conditional 3D Pix2Pix for Healthy Tissue Inpainting in Brain MRI
- • [BraTS-Inpainting] Anatomy-Aware Healthy Brain Inpainting: Integrating Tissue Guidance Across Inputs, Features, and Objectives
- • [BraTS-Inpainting] Now You Have My Healthy Attention: A U-DiT for Brain-MRI Inpainting
- • [BraTS-Inpainting] An SSIM-Prioritized 3D Attention U-Net for Synthetic Brain Inpainting
- • [BraTS-Inpainting] Mask-Guided 3D U-Net with Component-Wise Tiled Inference for Healthy Brain Tissue Inpainting
- • [BraTS-Inpainting] Geometry-Aware Conditional 3D Wavelet Diffusion for Pseudo-Healthy Brain MRI Inpainting
- • [BraTS-Inpainting] RARF: Region-Aware Rectified Flows for 3D Brain MRI Inpainting
- • [BraTS-Inpainting] Glioma Inpainting in Brain MRI via 3D Region Aware Diffusion
- • [BraTS-Inpainting] Sharpening the Ensemble: An SSIM-Aligned Residual Refiner for Brain-MRI Inpainting Post-Processing
- • [BraTS-Inpainting] A Mask-Gated 3D U-Net with Void-Size Conditioning for Healthy Tissue Inpainting in Brain MRI
- • [BraTS-Inpainting] CATCH: Counterfactual Anatomical Tissue Inpainting with Conditional Haar Diffusion
- • [BraTS-Inpainting] Retrieval-Augmented Wavelet Diffusion for Local Synthesis of Healthy Brain Tissue
- • [BraTS-Inpainting] RESIN: Residual Synthesis for Healthy-Tissue Inpainting in Brain MRI
- • [BraTS-METS] Clinically Informed, Dataset-Adaptive Lightweight Segmentation of Brain Metastases within the nnU-Net Framework
- • [BraTS-METS] A Multi-Network Ensemble Strategy for the BraTS 2026 Brain Metastasis Segmentation Challenge
- • [BraTS-METS] Lesion-Aware Hybrid State-Space and Residual-Encoder Fusion for Brain Metastasis Segmentation
- • [BraTS-METS] Integrating nnDetection and nnU-Net for Brain Metastasis Segmentation in the BraTS-METS 2026 Challenge
- • [BraTS-METS] Rare-Region Optimization and Ensemble Composition for Pre- and Post-Treatment Brain Metastases Segmentation
- • [BraTS-METS] Runtime-Aware Ensemble Optimization for Brain Metastasis Segmentation under Strict Deployment Constraints
- • [BraTS-METS] Region-Aware Residual Encoder nnU-Net for Multi-Region Brain Metastasis Segmentation
- • [BraTS-METS] Pre- and Post-Treatment Brain Metastases Segmentation Using nnU-Net with Post-Processing for BraTS 2026
- • [BraTS-METS] Beyond Aggregate Dice: Size-Stratified Failure Analysis of an nnU-Net Baseline for Brain Metastasis Segmentation
- • [BraTS-METS] Gated Frequency-Enhanced Class-Wise Ensemble for Brain Metastases Segmentation
- • [BraTS-METS] Brain Metastasis Segmentation Using an Ensemble of U-Mamba Models
- • [BraTS-METS] A Region-Based Residual-Encoder nnU-Net Ensemble with a Matched-Normalization Subtraction Channel and Resection-Cavity False-Positive Suppression for Brain Metastasis Segmentation
- • [BraTS-METS] A Transformer Pipeline with Uncertainty-Guided Curation and Failure Recovery for Brain Metastases Segmentation
- • [BraTS-METS] Ensemble nnU-Nets for pre- and post-operative Brain Metastases Segmentation in BraTS 2026 Task 1
- • [BraTS-METS] Region-Wise Logit Fusion and Utility-Gated Refinement for Brain Metastasis Segmentation
- • [BraTS-METS] Scale-Aware 3D Deep Learning for Robust Brain Metastasis Detection in Multimodal MRI
- • [BraTS-METS] Resection-Cavity-Aware Segmentation of Brain Metastases for BraTS 2026
- • [BraTS-METS] Segmentation of Pre- and Post-treatment Brain Metastases Using an Ensemble of MRI Foundation Models
- • [BraTS-METS] CarveMix-RC: Addressing Rare-Class Imbalance Through Lesion-Aware Synthetic Augmentation for Brain Metastasis Segmentation
- • [BraTS-METS] Detege et Delinea: A Two-Stage Framework for Brain Metastasis Detection and Segmentation in Multimodal MRI
- • [BraTS-METS] Region-Aligned Training and Target-Specific 2D–3D nnU-Net Fusion for BraTS 2026 Brain Metastasis Segmentation
- • [BraTS-METS] A Residual-Encoder nnU-Net Baseline for Pre- and Post-Treatment Brain Metastasis Segmentation
- • [BraTS-METS] Seeing Lesions, Not Voxels: A Connected-Component-Weighted Dual-Map Focal Loss and Per-Group Oversampling for Brain Metastases Segmentation and Detection
- • [BraTS-METS] Brain Metastases Segmentation for BraTS 2026 Task 1: A Multi-Architecture Comparison
- • [BraTS-METS] Missing Modality Imputation and Brain Metastasis Segmentation via Latent-Space Ensemble Synthesis and Size-Aware Focal Loss
- • [BraTS-METS] Precision Over Recall: Brain Metastasis Segmentation with a Learned False-Positive Rejector
- • [BraTS-METS] ACORN: Asymmetric Conditional Overlapping RAVSS Network for Segmenting Small Brain Metastases
- • [BraTS-METS] Epistemic Uncertainty-Guided Supervision Weighting for Brain Metastasis Sub-region Segmentation
- • [BraTS-METS] METS-PRO R2: Lesion-Aware Positive Residual Refinement for Brain Metastasis Segmentation
- • [BraTS-METS] Segmentation of Pre- and Post-treatment Brain Metastases Using Ensemble Model
- • [BraTS-METS] Inference-Time Decoding for Brain Metastasis Segmentation
- • [BraTS-METS] A Detection-Aware SegResNetDS Ensemble and a Measured Null Space for Brain Metastasis Segmentation in BraTS 2026
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• [BraTS-PEDs] Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge (BraTS-PEDs) 2026: Design and Results
- Jiang, Zhifan; Fathi Kazerooni, Anahita; Astaraki, Mehdi; Bakas, Spyridon; Chung, Verena; Farahani, Keyvan; Correia de Verdier, Maria; Baid, Ujjwal; LaBella, Dominic; Conte, Gian Marco; You, Suhang; Yordanov, Nikolay; Aboian, Mariam S.; Buzduga, Paula; Grosskopf, Erik; Kofler, Florian; Wiestler, Benedikt; Menze, Bjoern; Huang, Raymond Y.; Batal, Fadel; Varshochi, Sanaz; Adib Moradi, Sahand; Sheth, Nakul; Nandolia, Khanak; Sánchez-Montaño, Mariana; Ware, Jeffrey B.; Nabavizadeh, Ali; Vossough, Arastoo; Linguraru, Marius George;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [BraTS-PEDs] Anatomy-Preserving Rare-Subtype Adaptation for Pediatric Brain Tumor Segmentation
- • [BraTS-PEDs] Two-Track Ensembling for Pediatric Brain Tumor Segmentation: Class-Specific Fusion and Voxel-Wise Intersection for Rare Subregions
- • [BraTS-PEDs] YOLO-UNet: A Hybrid YOLO-Encoder / U-Net-Decoder Network with a Full-Resolution Residual Boundary Branch for Pediatric Brain Tumor Segmentation
- • [BraTS-PEDs] LoG-Augmented nnU-Net Ensemble for Pediatric Brain Tumor Segmentation
- • [BraTS-PEDs] NeuroTS-Net: Multi-Class Semantic Segmentation of Pediatric Brain Tumors in Multi-Modal MRI
- • [BraTS-PEDs] Stable Boundary Anchoring and Per-Class Champion Source Composition for Pediatric Brain Tumor Segmentation in BraTS-PEDs
- • [BraTS-PEDs] AFS-Net: Adaptive Fusion Skip Network for Pediatric Brain Tumor Segmentation
- • [BraTS-PEDs] HREF: Hierarchical Region-Expert Fusion Framework for Accurate Pediatric Brain Tumor Segmentation
- • [BraTS-PEDs] Adapting PTransBTS for Pediatric Brain Tumor Segmentation in BraTS-PEDs 2026
- • [BraTS-PEDs] Hierarchical nnU-Net Logits for Pediatric Brain Tumor Subregion Segmentation
- • [BraTS-PEDs] Sub-Region-Specific Deep Learning Model for Pediatric Brain Tumor Segmentation on Multi-Parametric MRI
- • [BraTS-PEDs] Mechanism-Aware Post-Processing Under a Submission Budget: FLAIR-Viaevum at the BraTS 2026 METS, PEDs and GoAT Challenges
- • [BraTS-PEDs] Pediatric Brain Tumor Segmentation with MedSwinNet
- • [BraTS-PEDs] Brain Extraction, Residual-Encoder Ensembling and Metric-Aware Component Filtering for Pediatric Brain Tumor Segmentation
- • [BraTS-PEDs] Reliability-Weighted Supervision with Class Frequency Correction for Pediatric Brain Tumor Segmentation
- • [BraTS-PEDs] Modelling the Infiltrative Margin as a Graded Target: Reaction–Diffusion Soft Labels and Region-Specific Ensembling for Paediatric Brain Tumour Segmentation
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• [BraTS-Path] Histopathologic Brain Tumor Sub-region (BraTS) Classification Challenge 2026: Design and Results
- You, Suhang; Thakur, Siddhesh; Astaraki, Mehdi; Toth, Alexander; Chung, Verena; Baid, Ujjwal; LaBella, Dominic; Correia de Verdier, Maria; Jiang, Zhifan; Yordanov, Nikolay; Menze, Bjoern; Suero-Molina, Eric; Cherkezov, Asan; Kiolbassa, Nora Maren; Cooper, Lee A. D.; Ahrendsen, Jared T.; Ali, Seemaab; Babaoglu, Berrin; Balcı, Serdar; Ballester, Leomar Y.; Barresi, Valeria; Fernández Klett, Francisco; Gubbiotti, Maria A.; Harmsen, Hannah; Hortobagyi, Tibor; Kulac, İbrahim; López, Giselle Y.; Lucas, Calixto-Hope G.; Majeed, Marwan M.; Miller, Michael L.; Miletić, Hrvoje; Nasrallah, MacLean P.; Phillips, Joanna J.; Reimann, Regina Rose; Rodriguez, Michael; Rodriguez, Fausto J.; Satgunaseelan, Laveniya; Schweizer, Leonille; Stan, Alexandru-Constantin; Sun, Yu; Zanazzi, George; Huang, Raymond Y.; Farahani, Keyvan; Aboian, Mariam S.; Linguraru, Marius George; Bell, William R.; Huse, Jason; Bakas, Spyridon;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [BraTS-Path] Neuropathology in the embedding space of glioblastoma heterogeneity: identifying classification-relevant signals with machine learning
- • [BraTS-Path] Dual-LoRA Adaptation of Pathology Foundation Models for Glioblastoma Histologic Pattern Classification
- • [BraTS-Path] Patch-Level Glioblastoma Subregion Classification with Foundation Model and Hierarchical Balanced Sampling
- • [BraTS-Path] Beyond Frozen Features: Block Expansion of Pathology Foundation Models for Glioblastoma Sub-Region Classification
- • [BraTS-Path] Ensemble of Pathology Foundation Models for Fine-Grained Histologic Classification of Glioma
- • [BraTS-Path] Leakage-Free Patient-Grouped Evaluation of Frozen Pathology Foundation Models for Long-Tailed Glioma Sub-region Classification
- • [BraTS-Path] Rare-Class Conditional Routing with Foundation Model Representations for Glioma Histologic Sub-region Classification
- • [BraTS-Path] Pathology Foundation Models Under Class Starvation and Distribution Shift: NeuroForge at the BraTS 2026 Pathology Challenge
- • [BraTS-Path] Foundation-Model Ensembling with Vision–Language-Informed Representations for Glioblastoma Subregion Classification
- • [BraTS-Path] GLAD-Net: Adaptive Multi-Teacher Distillation of Vision Foundation Models for Fine-Grained Glioma Histopathology
- • [BrainWorks] From Edge to Gradient: Quantifying the Infiltrative Margin in Paediatric Diffuse Glioma
- • [BrainWorks] Hierarchical Differential MedViT-3D: Specialized Hybrid Transformer for Multiclass Diagnosis of Neurodegenerative Diseases
- • [BrainWorks] Unsupervised Anomaly Detection in Pediatric Brains: Method Comparison Across Multiple Clinical Conditions
- • [BrainWorks] BrainMRI-CLIP: Enhancing Brain MRI Representation Learning via Joint Vision-Language-Diagnosis Alignment
- • [BrainWorks] Group ICA 2.0: Closing the Gap Between Subjects and Group Latent Decomposition
- • [BrainWorks] Reliability-aware Multimodal Fusion for Brain Tumor Segmentation
- • [BrainWorks] Direct Mask-Perturbation Auditing for Geometry-Derived Brain Lesion Biomarkers
- • [BrainWorks] Pre-Operative to Intra-Operative: A Brain Tumor Segmentation Generalization Study
- • [BrainWorks] Reconstruct and Distill: A Hybrid Masked-Autoencoder and Self-Distillation Foundation Model for Clinical Brain MRI
- • [BrainWorks] CASA-Net: Confidence-Aware Spatial Attention Network for Efficient Detection-Guided Brain Tumor Segmentation
- • [BrainWorks] Bidirectional Propagation Makes Sparse Re-Prompting Viable in Zero-Shot SAM2 for Whole-Tumor Glioma Segmentation
- • [BrainWorks] RBT-Faz: Register-Bottleneck 3D Swin-UNETR with Clinical Text Alignment for Ordinal Fazekas Grading from FLAIR MRI
- • [BrainWorks] UPStaiN: Unsupervised Population-Based Morphology-Aware Stain Normalization
- • [BrainWorks] Self-supervised Learning for 3D Light-Sheet Microscopy Image Segmentation based on DINO-v2 and nnU-Net
- • [BrainWorks] DeepNucleiNet: Encoding Spatial Nuclear Patterns for Data-Efficient Necrosis Detection in Computational Neuropathology
- • [BrainWorks] Scaling Native 3D Self-Supervised DINOv2 for Brain MRI Foundation Models
- • [CAPI-WOMEN] Panda: Unsupervised Pelvic Anomaly Detection for Real-Time MR Imaging
- • [CAPI-WOMEN] Comparing Problem Formulations for Endometriosis Lesion Detection on T2-weighted Pelvic MRI
- • [CAPI-WOMEN] Interactive Foundation Models for 3D MR Uterus Segmentation: Performance and Limitations
- • [CAPI-WOMEN] Cross-Modal MRI Ovary Segmentation in Endometriosis Using Unpaired TVUS Prototype Priors
- • [CAPI-WOMEN] A Multi-Site Label Trap in Shape-Based Endometriosis Detection: What Female Pelvic-Organ Shape Does (and Does Not) Encode
- • [CAPI-WOMEN] Multi-scale radiomics in pelvic MRI for endometriosis subtyping: highlighting data heterogeneity constraints
- • [CAPI-WOMEN] Patient-Level Data Leakage in Colposcopy Classification: A Cautionary Study with Evidential Uncertainty Quantification for Cervical Cancer Screening
- • [CAPI-WOMEN] Pelvic MRI Patient Verification with Foundation-Model Embeddings
- • [CAPI-WOMEN] PelviNeXt: A Modality-Agnostic Hybrid Network for Pelvic Imaging in Women’s Health
- • [CAPI-WOMEN] Unsupervised Adversarial Domain Adaptation for Uterine layer Segmentation: From Labeled Cine to Unlabeled Dynamic EPI MRI
- • [CAPI-WOMEN] Evaluating the Prompt-to-Automation Gap: A Comprehensive Benchmark for Laparoscopic Endometriosis Segmentation
- • [CAPI-WOMEN] Pelvis-SigLIP: Benchmarking Vision-Language Models for Female Pelvic MRI Series Retrieval across Zero-Shot, Linear-Probe, and Fine-Tuning
- • [CARE] A Transfer-Learned Segmentation-to-Staging Cascade for Robust Liver Fibrosis Staging on Real-World Multi-Vendor MRI
- • [CARE] Myocardial Scar and Edema Segmentation with Partial Labels and LGE-Guided Rescue
- • [CARE] Iterative Human-in-the-Loop Learning for Accurate Segmentation of Liver
- • [CARE] Improving Cross-Site Whole-Heart Segmentation
- • [CARE] Topology-Guided Lightweight 2.5D Liver Segmentation for Limited-Annotation Multi-Center Fibrosis MRI
- • [CARE] Fibrosis-Aware Spatial-Temporal Representation Learning for Liver Fibrosis Staging from Real-World MRI
- • [CARE] MaskSAM-PBPR: A Prior-Guided Bidirectional Propagation Refiner for Multi-Sequence CMR Myocardial Pathology Segmentation
- • [CARE] ABMP-Net: Abnormality-Aware Bidirectional Motion-Physics Network for Cine CMR-Based Myocardial Scar Segmentation
- • [CARE] AGSW-LAMS: Adaptive Gaussian Soft Windowing for Left Atrial Multi-Structure Segmentation
- • [CARE] Beyond Cavity Constraints: A Systematic Evaluation of Spatial Priors in Cascaded Left Atrial Scar Segmentation
- • [CARE] Wall-Band Anatomical Prior-Guided 3D nnU-Net for Left Atrial Scar Segmentation in LGE-MRI
- • [CARE] DOVE: Domain-Robust Ordinal Evidence Learning with 2.5D Multiple Instance Learning for MRI-Based Liver Fibrosis Staging
- • [CARE] Progressive Optimization of UU-Mamba for Left Atrial Multi-Structure Segmentation in CT
- • [CARE] Structure-Reliability-Guided ROI and Donor Fusion for Multi-Center MR Whole-Heart Segmentation
- • [CARE] CIRSeg: Coarse-to-Fine Intensity-Robust Liver Segmentation with Source-Free Continual Test-Time Adaptation
- • [CARE] ROI-Guided Dual-Channel Data Construction and Ensemble Learning for Left Atrium Segmentation in the CARE 2026 Challenge
- • [CARE] Dual-Task Multi-Sequence MRI Framework: 3D Segmentation and Ensembled Fibrosis Staging of the Liver
- • [CARE] Pseudo-Label-Enhanced Liver Segmentation and Mask-Guided Patch Learning for Fibrosis Staging Classification
- • [CARE] A Unified Registration-Guided 3DINO Framework for Semi-Supervised Liver Segmentation and Patch-Based Liver Fibrosis Staging under Missing Modalities
- • [CARE] MoSAIC: Motion and Supervision-Aware Inference for Myocardial Scar and Edema Segmentation from Multi-Sequence and Cine CMR
- • [CARE] SCALA: Semi-supervised Cascade for Left Atrial Scar, Cavity, and Multi-Structure CT Segmentation
- • [CARE] Vendor-Robust Liver Segmentation and Fibrosis Staging from Multi-Phase MRI
- • [CARE] Foundation Model Augmented Mixture-of-Experts with Diffusion Augmentation for Robust Cardiac Myocardial Pathology Segmentation
- • [CARE] Left Atrial Scar Quantification from LGE-MRI: A Controlled Ablation and Detectability Study
- • [CARE] Shared Multimodal Learning with Anatomical Pretraining for CT and MRI Whole-Heart Segmentation
- • [CARE] Stable Morphology, Unstable Deep Classifiers: Morphology-Guided Ranking in Unlabeled Liver MRI Cohorts
- • [CARE] LISynSeg: Data-Centric Label-to-Image Synthesis for Cross-Modality Whole-Heart Segmentation
- • [CARE] Causality-inspired Polar Approach for Myocardial Pathology Segmentation in Multi-sequence CMR
- • [CARE] Decoupling Supervision and Recoupling Context: Reliability-Aware Soft-Prior Learning for Myocardial Scar and Edema Segmentation
-
• [CLIP] AI-Based Maxillofacial Workflows Automated in 3D Slicer: Cross-Modal Registration, VFACE Facial Analysis, and Predictive Surgical Planning
- Buisson, Alexandre; Dumont, Paul; Ng, Janson; Sanna, Angelina; Ruellas, Antonio; Aliaga, Aron; Huang, Yanjie; Prieto, Juan Carlos; Al Turkestani, Najla; Yatabe, Marilia; Bianchi, Jonas; Pieper, Steve; Li, Tengfei; Zhu, Hongtu; Dai, Runpeng; Barone, Selene; Evangelista, Karine; Cevidanes, Lucia H.; Teixeira, Rodrigo; de Oliveira, Pedro José; Mattos, Claudia Trindade; Castro, Gabriela; Giudice, Amerigo; Gonçalves, João;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [CLIP] SegClass-CD: Segmentation-Guided Region-Based Classification of Crohn’s Disease Imaging Findings from Multi-Contrast MRE
- • [CLIP] Exempt-KL: Preserving Diagnostic Ambiguity for Reliable Medical Out-of-Distribution Detection
- • [CLIP] Domain-Adaptive Parameter Decoupling for Heterogeneous Vision-Language Retrieval
- • [CLIP] Sample-Adaptive Cross-Modal Expert Fusion for Robust Breast mpMRI Classification
- • [CLIP] Intraoperative Fully Automatic Registration of Fluoroscopic Image Pair: Cadaveric Evaluation
- • [CLIP] Differentiable Manifold Optimization for Fast, Multi-Needle Ablation Planning
- • [CLIP] GLR-MM: Graph-Based Global–Local Reconstruction for Robust Multimodal Chest X-ray and EHR Representation Learning under Missing Modalities
- • [CLiMeM] Continual Model Merging with Test-Time Adaptation for Whole-Slide Image Analysis
- • [CLiMeM] Investigating Test-Time Adaptation of Convolutional Neural Networks for Medical Image Analysis under Distribution Shifts
- • [CLiMeM] Integrating Uncertainty and Latent Feature Diversity for Robust Memory Replay in Continual Medical Imaging Learning
- • [CLiMeM] How Resilient are Foundation Segmentation Models to Noisy Ultrasound Artifacts? A Multi-Dataset Benchmark Across Prompts, Noise Types, and Severity Levels
- • [CLiMeM] An Empirical Analysis of Continual Learning for Heterogeneous Medical Visual Question Answering
- • [CLiMeM] Learning to Reason Over Physician Corrections: An Interactive Agentic Framework for 3D Tumor Segmentation
- • [CLiMeM] Multimodal Fusion for Domain-Incremental Continual Learning in 3D Medical Imaging
- • [CMMCA] Zero-Shot Ultra-Quality 4D-MRI Motion Reconstruction Framework Based on Augmented Digital Phantom Pre-Training
- • [CMMCA] Shared-Private Subspace Decomposition for Multi-Task Lung Cancer Classification in CT
- • [CMMCA] D2TMIL: Disentangled Dual-Task Multiple Instance Learning for 1p/19q Status Prediction from Whole Slide Images
- • [CMMCA] Bridging Slices to Volumes: Anatomy-Guided Slice-Consistent Latent Diffusion with Local Correlated Noise for MR-to-CT Synthesis
- • [CMMCA] Nerve-Centric Heterogeneous Graph Learning for Tumor–Nerve Interaction Modeling in Survival Prediction
- • [CMMCA] The Glioma Epigenome as a Potential Landscape: A Continuous G-CIMP Erosion Coordinate that the Methylation Class Discards
- • [CMMCA] TriSCoV-Net: Cross-Scale Verified Virtual Immunomarker Proxy Generation from Diffusion Magnetic Resonance Imaging
- • [CMMCA] Free-breathing Time-resolved Cine MR Fingerprinting Using Self-supervised Motion Navigation for Liver Cancer Radiotherapy
- • [CMMCA] OncoRelay3D: Foundation-Model-Assisted Reconstruction of 3D Tumor Cell-Expression Fields for Mechanism-Aware Directed Cell-Cell Communication
- • [CMMCA] Pulmonary Vascular Fractal Dimension on Non-Contrast Planning CT as a Potential Imaging Biomarker for Early Radiation-Induced Lung Injury: A Multi-Scale Structural Analysis
- • [CMMCA] A Differentiable Brain Tumor Mass Effect Solver
- • [CMRSeg] A Multi-scale DINOv3-based Pipeline for Multi-view Cardiac MRI Segmentation
- • [CMRSeg] NATA-Net: A Network with Adaptive Task-Aware Heads for Universal Cardiac MRI Segmentation
- • [CMRSeg] View-Specialized Hybrid Segmentation for Multi-View Cardiac MRI: Combining nnU-Net, CineMA, and Scar-Elastic Refinement
- • [CMRSeg] Acquisition-Structured nnU-Net Ensembles for Multi-Sequence Cardiac MRI Segmentation and Quantification
- • [CMRSeg] View-Specialized CMR-MULTI Segmentation with Metric-Gated Clinical Output Calibration
- • [CMRSeg] CardioMix: A Unified Framework for Multi-Sequence and Multi-View Cardiac MRI Segmentation
- • [CMRSeg] nnU-Net for Cardiac MRI Segmentation and Scar Quantification (Cine + LGE): CMR-Multi 2026
- • [CMRSeg] Foundation Models Adaptation for Multi-View Multi-modal Cardiac MRI Segmentation and Direct Ejection Fraction Estimation
- • [CMRSeg] Per-View Specialist Networks for Multi-Sequence, Multi-View Cardiac MRI Segmentation and Clinical Quantification: A Comparison of nnU-Net and MedNeXt Backbones
- • [CMRSeg] Multi-View CMR Segmentation with Clinical Quantification for Cine and LGE: Vista3D and DINOv2-DPT
- • [CMRSeg] CardioWorld-GQ: An Observation-Conditioned Cardiac Imaging World Model with a Differentiable Clinical Readout and Calibrated Endpoint Uncertainty
- • [CMRSeg] DINO-CMR: DINOv3-Driven View-Hybrid Segmentation with Decoupled Measurement for Multi-Sequence CMR
- • [CMRSeg] An Auditable Geometry Contract for Multi-View Cardiac Magnetic Resonance Imaging Analysis
- • [CMRSeg] Geometry-Aware View Routing with Hybrid 2.5D–3D Context for Multi-View Cine CMR Segmentation
- • [CMRSeg] Anatomy-Prior Guided Decoupled Expert Networks for Multi-View Cardiac MRI Segmentation and Biomarker Estimation
- • [CMRSeg] Native-Resolution Multi-Sequence Cardiac MRI Segmentation for Accurate LVEF and Scar Quantification
- • [CMRSeg] CardioState: Task-Aligned 2.5D MedNeXt for Multi-Sequence Cardiac MRI Segmentation and Quantification
- • [CMRxRecon2026] FlowMRI-Net++: A Unified Sampling-Aware 4D Flow MRI Reconstruction Network with Zero-Shot Adaptation
- • [CMRxRecon2026] CUT-4DFlow for Accelerated 4D-Flow MRI Reconstruction
- • [CMRxRecon2026] Curriculum Learning and ROI-Aware Supervision for Highly Accelerated 4D Flow MRI Reconstruction
- • [CMRxRecon2026] Residual-Gated Data Consistency and Phase-Locked Magnitude Refinement for Accelerated 4D Flow MRI
- • [CMRxRecon2026] Separating Aliasing from Flow: Temporal-Frequency Regularization for Unrolled 4D flow MRI Reconstruction
- • [CMRxRecon2026] FlowMoDL: Model-Based Deep Learning with Conjugate-Gradient Data Consistency for Highly Accelerated 4D Flow MRI Reconstruction
- • [CMRxRecon2026] Stage-Aligned Knowledge Distillation for Fast and Memory-Efficient 4D Flow MRI Reconstruction
- • [CMRxRecon2026] Keep the Encodings Apart: Per-Encoding Complex-Valued Variational Networks for Accelerated 4D Flow MRI
- • [CMRxRecon2026] Subspace-Guided Upstream-Downstream Deep Learning Reconstruction for Fast 4D Flow MRI
- • [CMRxRecon2026] Phase-Coupled State-Space Reconstruction for Ultra-Accelerated 4D Flow MRI
- • [CMRxRecon2026] Spatiotemporal Context-Informed Unrolled Complex Reconstruction Networks for 4D Flow MRI
- • [CMRxRecon2026] Complex-Valued and State-Augmented Variational Networks for Accelerated 4D Flow MRI Reconstruction
- • [CMRxRecon2026] Joint Supervised and Self-Supervised Training with Acquisition-Robust Techniques for Accelerated 4D Flow MRI Reconstruction
- • [CMRxRecon2026] SDUM-Flow: Data Synthesis and Augmentation for Robust Unrolled 4D flow MRI Reconstruction
- • [CMRxRecon2026] CLEAR: Complex Learned Explicit Analytical Regularization for Ultra-Accelerated 4D Flow CMR Reconstruction
- • [CMRxRecon2026] Lifting 2D Diffusion Priors to 4D Flow MRI: DPS with Cross-Frame Prior Propagation and Cyclic Pass
- • [CMRxRecon2026] VeloSubspace: Phase-Aware Training-Free Reconstruction for Highly Accelerated 4D Flow MRI
- • [CMRxRecon2026] Joint Multi-Velocity FlowVN Reconstruction with Flow-Aware Supervision for Accelerated 4D Flow MRI
- • [CMRxRecon2026] Prompt4D-MVE: A Lightweight Parameter-Shared Cascade with Magnitude–Velocity Experts for Highly Accelerated 4D Flow MRI
- • [COMPAYL] How Much Information Is Enough? A Benchmark of Foundation Models for Thyroid Histopathology under Limited Patch Sampling
- • [COMPAYL] ProtoDiffSurv: Differential Prototype Learning for Weakly Supervised Survival Analysis
- • [COMPAYL] When Histopathology Images Degrade: A Robustness Benchmark for Pathology Foundation Models
- • [COMPAYL] Distance-Guided Vision Transformer based Foundation Model for Fluorescence Nuclei Instance Segmentation
- • [COMPAYL] FIRB: Fusion, Interaction and Robustness Benchmark for Multimodal Learning in Computational Pathology
- • [COMPAYL] Learning to Organ-ize: Low-resolution Tissue Segmentation for Preclinical Toxicological Pathology
- • [COMPAYL] Vision-Language Models as Zero-Annotation Oracles in Histopathology
- • [COMPAYL] Modeling Intra-spot Cellular Context for Histology-to-Spatial Transcriptomics Prediction
- • [COMPAYL] NegZoom: Negative-Constraint Coarse-to-Fine Retrieval in Whole Slide Images
- • [COMPAYL] Local Validation and Workflow Integration of Pathology Foundation Models for Colorectal WSI Classification
- • [COMPAYL] Linearized MIL Attention Reveals a Traversable Direction in the Virchow2 Embedding Space
- • [COMPAYL] CIPS-Net: Text-Instructed Conditional Nucleus Instance Segmentation Network in Histopathology
- • [COMPAYL] CoDiR: Confidence-Guided Diffusion Refinement for Semi-Supervised Histopathology Segmentation
- • [COMPAYL] RetroScope: An Open Framework for Motorizing and Digitizing Vintage Microscopes
-
• [COMPAYL] Beyond Classification: Pathology Foundation Models as Detection Encoders for Mitotic Figures
- Banerjee, Sweta; Teimoury, Alireza; Porsche, Nils; Stoll, Alexandra K.; Weiss, Viktoria; Hargarter, Niklas; Ammeling, Jonas; Conrad, Thomas; Stroblberger, Christoph; Kaltnecker, Christopher; Klopfleisch, Robert; Bertram, Christof A.; Breininger, Katharina; Aubreville, Marc;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [COMPAYL] IMILIA: interpretable multiple instance learning for inflammation prediction in IBD from H&E whole slide images
- • [COMPAYL] Bidirectional Translation Between ISH and H&E Glioblastoma Tissue Sections via Attention-Enhanced CycleGAN
- • [COMPAYL] ProBAG: Prototype-Guided Boundary-Aware Graph Diffusion for Weakly Supervised Histopathology Segmentation
- • [COMPAYL] Morphospatial Phenotyping of p21-Positive Hepatocytes in Chronic Liver Disease
- • [COMPAYL] Program-space Diffusion for Morphology-to-Transcriptomics Prediction
- • [COMPAYL] What Do Pathology Foundation Models Learn Beyond Gleason Grade in Prostate Cancer?
- • [COMPAYL] PathTrace: A Trace-Based Evidence Harness for Auditing Whole-Slide Pathology Agents
- • [COMPAYL] Investigation of Factors Contributing to Domain Generalization in Single-Shot Autofocus
- • [COMPAYL] Disentangled Shared Representations Improve Morpho-Transcriptomic Integration
- • [COMPAYL] Investigating Test-Time Training for Patch Classification in Pathology
- • [COMPAYL] CLEAR-WSI: Towards Foundation-Model-Empowered Diagnosis Aligned Whole Slide Image Retrieval
- • [COMPAYL] AutoVLAK - An Automated Pipeline for Vision-Language Knowledge Base Curation from Open-Access Medical Literature
- • [COMPAYL] A Benchmark of Foundation Models for Chemotherapy Response Scoring in High-Grade Serous Ovarian Cancer
- • [COMPAYL] Beyond the capture area: Imputation of spatial gene expression from H&E
- • [COMPAYL] Multi-scale Fusion of Fast Vision Mamba and Foundation Model Features for Patch-Level Gleason Grading in Computational Pathology
- • [COMPAYL] Virtual immune cell prediction from H&E Whole Slide Images
- • [COMPAYL] Post-hoc Shrinkage of Acquisition-Induced Variability in Histopathology Vision Foundation Model Embeddings
- • [COMPAYL] Unified Multimodal Fusion for Cancer Survival Prediction: A Missing-Robust Framework across Histopathology, Radiology, Genomics, and Clinical Data
- • [COMPAYL] Morphology-Preserving Virtual Staining from H&E to PAS and IHC using Enhanced Diffusion Models
- • [COMPAYL] Dual-CellNucDETR: Context-Aware Object-Level Cell Analysis
- • [COMPAYL] HemaHier: Chain-Conditioned Ordinal Hierarchies for Lineage-Aware Bone-Marrow Cytology
- • [COMPAYL] Act or defer? Multimodal intraoperative diagnosis of CNS tumours: A proof-of-concept study
- • [COMPAYL] QLabelMIL: Inter-Pathology Query Decoding for Multi-Label Gastric Histopathology
- • [COMPAYL] QUERY-ST: Language-Guided Retrieval Across Histology and Spatial Transcriptomics
- • [COMPAYL] Lymphocyte Mimicry Correction via Region-Level Tissue Reasoning and Unbalanced Optimal Transport
- • [COMPAYL] Thumbnail-Based Tile Selection for Efficient Whole-Slide Image Classification in Resource-Limited Pathology
- • [COMPAYL] Semantic-Guided Multimodal Preprocessing for Vision Transformer-Based Clear Cell Renal Cell Carcinoma Grading
- • [COMPAYL] DreaMS-Align: Zero-Shot Spectrum-Embedding Surrogates for Scalable WSI-MSI Co-registration
- • [COMPAYL] ReferralSeg: A Multi-Cancer Benchmark for Clinician-Style Language-Guided Segmentation in Histopathology
- • [COMPAYL] MIST: Multimodal Survival Prediction with Genomic-Guided Histology Attention
- • [COMPAYL] When RNA is Missing: A Multimodal Fusion Benchmark for BCG Progression Prediction in HR-NMIBC
- • [COMPAYL] AI-Based Ki67 Quantification for Triage of Genomic Recurrence Score in Breast Cancer
- • [COMPAYL] PaiXBench: Benchmarking Vision-Language Models under Real-World Conditions
- • [COMPAYL] OrdPath-MIL: Ordinal Multiple Instance Learning for Pathology Whole-Slide Image Grading
- • [COMPAYL] Explainable Slide-Level Analysis for High-Risk Disease in Colorectal Polyps using Foundation Models
- • [COMPAYL] PathPool: Decoupled and Pooled Feature Serving for Pathology Foundation Models
- • [CREATE] FRAME: Full-body Recovery via Adaptive Margin Extension for Occlusion-Robust 3D Human Pose and Shape Estimation
- • [CREATE] StereoSurg: A Benchmark for Stereo Depth Estimation in Surgical Scenes
- • [CREATE] Predictive Representation Learning with Prior Knowledge for Surgical Workflow Forecasting
- • [CREATE] CLMP: Contrastive Language-MRI Pretraining at Large Scale
- • [CREATE] EyeVQA: Benchmarking Ophthalmic Vision-Language Models from Recognition to Spatial Grounding
- • [CREATE] Surgical Foundation Model Ensembles for Predicting Annotator Disagreement in Critical View of Safety Assessments
- • [CREATE] Hierarchical Quality Assessment of Medical Image Synthesis for Clinical Translation
- • [CREATE] AI-Guided User Interface Enables Standardized Carotid Ultrasound Scanning After Minimal Training: A Comparative Experimental Study
- • [CREATE] SurgSemGS: Semantic and Contrastive Gaussian Splatting for Dynamic Surgical Scene Understanding
- • [CREATE] CathAgent: A Lightweight Video Assistant for Endovascular Action Recognition
- • [CREATE] Intraoperative AR Visualization of Preoperative (CB)CT via X-Ray Registration
- • [CREATE] CT Airway-Map Reliability for Bronchoscopic Planning: A Multi-Cohort Study of Connected Peripheral Endpoints
- • [CREATE] RadQC-Bench: Benchmarking Vision-Language Models for Quality Control in Radiology Reporting
- • [CaPTion] Evaluating the Effects of Inter-Observer and Model Variability on Radiological Peritoneal Cancer Index Assessment
- • [CaPTion] The provider-coverage gap in conformal ISUP grading is not a fixed property of the cohort: evidence from two grader configurations on PANDA
- • [CaPTion] Cross-Center Prototype Learning for Generalizable Multimodal Head-and-Neck Cancer Prognosis
- • [CaPTion] Efficient Self-Supervised Pre-Training in Endoscopy
- • [CaPTion] Learning Tissue Interactions for Pathological T-Staging of Rectal Cancer from Whole-Slide Images
- • [CaPTion] Performance vs Consistency: Evaluating a Foundation Model in Lung-RADS Screening
- • [CaPTion] Physics-Guided Implicit Neural Representations for Enhanced Quantitative DWI Biomarkers in Pancreatic Cancer
- • [CaPTion] Graph-Refined Probabilistic Mitigation and Fair Reweighing for Enhanced Equity and Generalizability in Prostate MRI Radiomics
- • [CaPTion] Causal-Adversarial Probing of Clinical Covariates for Prostate MRI Grading
- • [CaPTion] TRAIL: Trajectory-Aware Reward Attribution and Inference for Longitudinal Multiple Myeloma Treatment Trajectories
- • [CaPTion] Task-Guided Deformable Registration for Prostate MRI Analysis
- • [CaPTion] SGRNet: Spatially Guided Radiology Network for Structured Radiological Reporting of Head and Neck Cancer
- • [CaPTion] Cross-Modal Contrastive Learning for the Retrieval of Immunotherapy-Associated Molecular Signatures from Histopathology
- • [CaPTion] Confidence-Aware Multimodal Survival Prediction in Renal Cell Carcinoma using Graph-Based Histopathology Encoding
- • [CaPTion] Task-Specific Prostate MRI Quality Assessment via Downstream Performance and Feature-Space Novelty
- • [CaPTion] Radiomics–Foundation Fusion for Interpretable RCC Classification: Internal Benchmarking and Exploratory External Transfer
- • [CaPTion] When Two Tracers Disagree: An Investigation of Multimodal Fusion for Clinical PET/CT Segmentation
- • [CaPTion] SLN-Net: A Dual-Sequence MRI Network for Detecting Small Lymph Nodes in Gynecologic Malignancies
- • [CaPTion] Deep Learning-Based T4 Colorectal Cancer Staging from Preoperative CT Scans
- • [CaPTion] A Unified Multi-Organ Framework for Universal Lesion Detection, Segmentation and Longitudinal Tracking in CT Imaging
- • [CaPTion] DINOv2 for PET: A Pre-Training Domain Benchmark Across Classification, Segmentation, and Prognosis
- • [CaPTion] Identity-Preserving Synthetic Dermoscopic Lesion Generation via ABCD Prompting
- • [CaPTion] Domain-Specific Clinically-Grounded Multi-Task Learning for Interpretable Early Colorectal Cancer Recognition
- • [CaPTion] L-Spot: Slice-Aware Consensus for Hepatocellular Carcinoma Localisation in Contrast-Enhanced CT
- • [CaPTion] Attention-based prediction of lymph node status in pt1 CRC using a histopathology foundational model
- • [CaPTion] PET/CT Radiogenomic Mutation Prediction in Non-Small Cell Lung Cancer Using Multi-Label Learning
- • [CaPTion] FaithCLIP: Faithful Geometry-Derived Alignment for Text-Queryable Polyp Representations
- • [CaPTion] Fed-FGS: Domain-Generalized Federated Polyp Segmentation via Fourier Hard-Thresholding and Gradient Scaling
- • [CaPTion] Why Background is Important: Virtual Lesion Excision for Detecting Radiologically “Invisible” Prostate Cancer
- • [CaPTion] Probability-Based Lesion-Aware FN/FP Loss for Whole-Body PET/CT Tumor Segmentation
- • [CaPTion] Limited-FOV Liver Deformable Registration via Transformer-Based Point-Cloud Completion
- • [DEMI2026] Bayesian adaptively-weighted ensembles for few-shot abdominal segmentation
- • [DEMI2026] A Hierarchy of Training Strategies for Data-Scarce Medical Image Classification
- • [DEMI2026] Uni-Light: An Ultra-Lightweight Framework via Uncertainty-Aware Knowledge Distillation for Brain Tumour Segmentation
- • [DEMI2026] Quality-Controlled Keyframe Sampling using Endoscopic Foundation Models
- • [DEMI2026] FLAME-US: A Landmark-Guided Dataset for Quantitative Fetal Motion Analysis in Freehand Ultrasound
- • [DEMI2026] The Data Engineering Contract: A Formally Specified Pipeline for Generative Prostate MRI
- • [DEMI2026] CheXQuery: Anatomy and Condition Guided Radiology Report Generation under Limited Data
- • [DEMI2026] Structure-Aware Diffusion for Synthetic Fluoroscopic Video Generation
- • [DEMI2026] Training-Free Histopathology Classification via Confidence-Filtered DINOv2 Retrieval
- • [DEMI2026] Simple, Safe, and Overlooked: Reclaiming Sustainable Domain Generalization with Statistical Color Matching
- • [DEMI2026] Subspace-Based Auditing of Bottlenecks in Retinal Fundus Foundation Embeddings
- • [DEMI2026] Ultra Gym: Transforming Clinical 3D Ultrasound Volumes into Dynamic, Multi-Task Training Data
- • [DEMI2026] Label-Efficient Data Engineering for Reliable Orthopedic Radiograph Registry Construction Under Distribution Shift
- • [DEMI2026] Measuring Browser Webcam Gaze Honestly: A Capture-Clock Methodology and Open Reference Implementation
- • [DEMI2026] Depth-Enhanced LoRA-Tuned VLMs for Hand and Tool Keypoint Detection in Surgical Scenes
- • [DEMI2026] ROI-Based Image Captioning for Endoscopic Kidney Stone Characterization
- • [DEMI2026] Exploring World Models for Surgical Video Synthesis for Tool Localisation and Tracking
- • [DGM4MICCAI] From Sparse X-rays to 3D CT: Training-Free Reconstruction with Diffusion Priors
- • [DGM4MICCAI] FedDSR: Codebook-Based Distribution Alignment for Heterogeneous Federated CT Super-Resolution
- • [DGM4MICCAI] Making sparse labels reliable: validity-gated ROI guidance for medical image generation with conditional latent diffusion model
- • [DGM4MICCAI] PCaPaint: Prostate Cancer Inpainting by Mitigating Shortcut Learning
- • [DGM4MICCAI] A Unified Latent Diffusion for High-Fidelity Any-to-Any Brain Modality Synthesis
- • [DGM4MICCAI] When the Edit Changes the Patient: Measuring Identity Preservation in Counterfactual Retinal Images
- • [DGM4MICCAI] Weakly Supervised Lung Nodule Segmentation via Plug-and-Play Guidance of 3D Rectified Flow
- • [DGM4MICCAI] Patient-Adaptive Modality Attention for Multimodal Brain Tumor Synthesis via Latent Diffusion
- • [DGM4MICCAI] Recovering Progression Beyond the Identity Shortcut: A Schrödinger Bridge Framework for Longitudinal Brain-MRI
- • [DGM4MICCAI] Disentangled Retinal Fundus Synthesis with Non-Circular Vessel-Topology Evaluation
- • [DGM4MICCAI] Feature-Space Guided Diffusion for Realistic Ultrasound Image Synthesis
- • [DGM4MICCAI] Leveraging Multi-Representation Features from Diffusion Models for Unsupervised 3D Medical Image Segmentation
- • [DGM4MICCAI] Unpaired D-FF-OCT-to-Histopathology Translation for Rapid Kidney Biopsy Visualization
- • [DGM4MICCAI] Synthetic Data Generation for Automated Hair Instance Segmentation in Trichoscopy
- • [DGM4MICCAI] Diffusion-Based Synthesis of Complete 3D Biparametric Prostate MRI
- • [DGM4MICCAI] 2D Versus 3D Diffusion for In Silico Training of Interventional X-ray AI Models
- • [DGM4MICCAI] Large-Volume Conditioned 3D Latent Diffusion Models for CT Metal Artifact Suppression
- • [DGM4MICCAI] Generation of Breast Tumors’ Shear Wave Elastography Images from Corresponding Ultrasound Images with US2SWEdiff
- • [DGM4MICCAI] LaST-Diff: Latent Spatiotemporal Diffusion for Temporally Stable Echocardiography Video Segmentation
- • [DT4H] An AI-Driven Pulsation Method of pVADs for Cardiac Digital Twins
- • [DT4H] A High-Fidelity Cardiac Digital Twin for Assessing Rate-Dependent Responses: A Comparative Multi-scale Study of TT2 and Tomek Models in Stratified 3D Ventricles
- • [DT4H] VERPEX: Anatomical Landmark Extraction on 3D Vertebrae exploiting Segmentation Masks
- • [DT4H] Learning Cardiac Electrophysiology Digital Twins Through Agentic Discovery of Hybrid Structure
- • [DT4H] Automatic Patient-Specific Microwave Ablation Planning Accelerated by a Physics-Guided Deep Learning Model
- • [DT4H] Few-shot Deep Learning for Phase-Amplitude Aberration Correction in Transcranial Focused Ultrasound
- • [DT4H] tFUSOperator: Operator Learning for Transcranial Focused Ultrasound Digital Twins
- • [DT4H] 3D Digital Twin Visualization of Multiclass GRF-Based Gait Disorder Classification
- • [DT4H] PPIM: Pennes Physics-Informed Mamba for Heat-Source-Conditioned 3D Bioheat Simulation
- • [DT4H] Beyond Predictive Modeling: Toward Causal Digital Twins for Personalized Healthcare
- • [DT4H] Physics-Guided Synthetic High-Frequency Ultrasound Generation for Skin Layer Segmentation
- • [DT4H] Improving Anatomical Continuity in Synthetic Left Atrial LGE-MRI Using Inter-Slice Attention
- • [DT4H] From Treatment Choices to Tumour Trajectories: Proof-of-Concept in Preference-Aware Agentic Simulation for Digital Twins
- • [DT4H] Anticipatory Digital Twins for Online Head-and-Neck Adaptive Proton Therapy via Foundation-Model Registration
- • [DT4H] Observation-Anchored Selective Assimilation for Longitudinal Tumor-State Proxy Forecasting in Post-Treatment Glioma
- • [DT4H] PolyAge-DT: Missingness-Aware Multimodal Representation Learning for Aging Digital Twins
- • [DT4H] Cohort-Level Twinning in an Agent-Based Model of Metastatic Tumor Growth
- • [DT4H] PanOCT: A Unified OCT-based Whole-Eye Reconstruction Framework for Ocular Digital Twin Construction
- • [DT4H] Population-to-Personal Networks as an Interpretable Foundation for Multi-omics-Driven Health Digital Twins
- • [DT4H] Modeling Progression of Microwave Ablation Volumes by Neural Surrogates
- • [DT4H] When Measurement Conventions Masquerade as Calibration Gains in Cardiac Digital Twins
- • [DT4H] Rapid Electrophysiology Simulation and Inverse Optimization based on Multi-Task Surrogate Modeling for Cardiac Digital Twins
- • [DT4H] Patient-Specific Articulated Digital Twins from a Single Full-Body CT Scan
- • [DT4H] Region-Aware Temporal Super-Resolution for Interventional X-ray Imaging
- • [DT4H] Sex-specific signatures in cardiac anatomy and function in CMR-Derived Biventricular Digital-Twins
- • [DT4H] Toward Oncology Digital Twins: Leveraging LLMs for Automated Longitudinal Data Ingestion in Ovarian Cancer Care
- • [DT4H] Learning Temperature-Dependent Properties in Cryoablation with Differentiable Physics
- • [DT4H] Towards surgical digital twins: a soft-tissue phantom study on stiffness-ratio calibration for AR-guided interventions
- • [DT4H] 3D Computational Modeling of the Vascular Heat-Sink Effect in Microwave Ablation of Tumors Close to the Aorta
- • [DT4H] PedDiffusion: Multi-scale wavelet packet conditional diffusion for pediatric 12-lead ECG reconstruction from a single lead
- • [DT4H] A Digital Twin Framework for ICU Delirium Using SAITS-Based Patient State Embeddings
- • [DT4H] From PACS to Morphometrics: A Hospital-Integrated Workflow for Hip Digital Twin Research
- • [DeCaF] Class Prototype Alignment Concentrates Chest X-ray Representations in Federated and Pooled Training
- • [DeCaF] Gerchberg-Saxton Spectral Preprocessing as Empirical Leakage Mitigation in Simulated Federated Medical Imaging
- • [DeCaF] FOCUS: Federated Learning Optimized Convergence via Uncertainty-guided Sampling
- • [DeCaF] When Average Calibration Fails: Site-Conditional Federated Conformal Risk Control
- • [DeCaF] Personalized Federated Learning for Equitable Breast Cancer Detection in Underrepresented Pacific Islander Populations
- • [DeCaF] FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning
- • [DeCaF] Federated Chest X-ray Diagnosis under Label Heterogeneity via Disease-Aligned Prototype
- • [DeCaF] LAFFS: LASSO Assisted Federated Feature Selection
- • [DeCaF] NeuroFL: A Production Federated Learning Platform for Privacy-Preserving Brain-Health Research
- • [DeCaF] Federated Learning for Brain Arteriovenous Malformation Segmentation: A Feasibility Study Across Four Hospitals and Two Continents
- • [DeCaF] DeMICAF: A Decentralised Medical Imaging Compliance Assessment Framework
- • [DeCaF] Quantifying Membership Privacy Risk Using Shadow Model Membership Inference Attack: Observations from a Breast Cancer Use Case
- • [DeCaF] Federated LoRA Adaptation of BiomedCLIP Across Four International Chest X-Ray Cohorts
- • [DeCaF] Towards Highly Heterogeneous Federated Learning: A Graph-Based Framework for Architectural and Data Heterogeneity
- • [Deep-Brea3th] Gradient-Based Latent Decomposition Reveals Mechanisms of Feature Degradation in Weakly Supervised Mammography
- • [Deep-Brea3th] Beyond 3D Convolutions: A 4D Spatiotemporal Transformer-Based Network for Capturing Vascular Kinetics in Neoadjuvant Chemotherapy Response Prediction
- • [Deep-Brea3th] Landmark Detection for Automated Mammography Positioning Quality Assessment via Posterior Nipple Line Consistency
- • [Deep-Brea3th] MammoClaw: Towards Skill-Evolving Agent Harness for Breast Cancer Mammography Analysis
- • [Deep-Brea3th] How Far Does Contrastive Self-Supervision Get You on Breast Ultrasound? A Label-Efficiency Study on BUSI
- • [Deep-Brea3th] Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- • [Deep-Brea3th] Adaptive Multi-Encoder Gated Fusion for Interpretable Prediction of Pathological Complete Response in Breast Cancer
- • [Deep-Brea3th] Mammo2Tomo: Adapting Mammo-CLIP to learn text-aligned DBT volume representations
- • [Deep-Brea3th] Forecasting Artifacts in High b-Value DWI MIP Images of the Breast Using Deep Learning and T2-Weighted or Low b-Value Acquisitions
- • [Deep-Brea3th] SAM-Guided Probability Representation for Breast Ultrasound Lesion Segmentation
- • [Deep-Brea3th] Quality-Aware Multi-class Breast MRI Segmentation Workflow
-
• [Deep-Brea3th] BreastMammo and DenseMammo: Benchmarks for Mammography Domain Generalization
- Pan, Hongyi; Durak, Gorkem; Aktas, Halil Ertugrul; Bejar, Andrea M.; Seker, Mustafa Ege; Alibeyoglu, Nebile; Guclu, Rumeysa; Bozkurt, Rana Gunoz Comert; Gurdal, Sibel Ozkan; Cabioglu, Neslihan; Ozcinar, Beyza; Yilmaz, Ravza; Ozmen, Vahit; Aribal, Erkin; Erturk, Sukru Mehmet; Zafari, Yalda; Mabrok, Mohamed; Batmanghelich, Kayhan; Yaqub, Mohammad; Xu, Ziyue; Bagci, Ulas;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [Deep-Brea3th] Fusion of Topological Data Analysis and Radiomics for High-Resolution 3D Breast Microcalcification Classification
- • [Deep-Brea3th] Multimodal Multiple Instance Learning for Fibroepithelial Tumor Diagnosis in Breast Ultrasound
- • [Deep-Brea3th] Shape-shifter: Generalized segmentation of breast implants on Localizer MRI
- • [Deep-Brea3th] OOD-Guided Continual Learning for Multi-Scanner Breast MRI Lesion Segmentation
- • [Deep-Brea3th] Structured Report Generation from Digital Mammograms via Instruction-Tuned LoRA Adaptation
- • [Deep-Brea3th] DAMST: Domain-Adaptive Medical Slice Transformer for Multi-Center Breast MRI Classification
- • [Deep-Brea3th] Impact of preprocessing strategies on segmentation of fibroglandular tissue on breast MRI using deep learning
- • [Deep-Brea3th] Healthy Counterfactual Generation via Diffusion Inpainting for Mammography Classification
- • [Deep-Brea3th] Breast MRI Sequence Type Classification using Convolutional Neural Networks
- • [Deep-Brea3th] Structure-State Conditioned FB-to-DIBH Transition Learning for Breast Cancer Radiotherapy Segmentation
- • [Deep-Brea3th] Image Reconstruction of Breast Diffuse Optical Tomography via Implicit Neural Representations
- • [Deep-Brea3th] A Multi-Stage Deep Learning Framework for the Automated Assessment of Mammographic Microcalcifications
- • [Deep-Brea3th] Towards Reliable Classification: Building Bridge From Validation to Clinics With Improved Partial-AUC Optimization for Mammography False-Positive Detections Filtering
- • [Deep-Brea3th] Mammo-LeJEPA: A Data-Efficient Self-Supervised Framework for Breast Density Estimation
- • [ELAMI] Rule-Compliant Brain MRI Volumetry Report Generation with Locally Deployable LLMs
- • [ELAMI] PSV2026: A Fine-Grained Clinical Factuality Dataset for Medical Vision-Language Models
- • [ELAMI] Contrastive Answer Calibration for Medical Visual Question Answering
- • [ELAMI] Diagnosis of Autism Spectrum Disorder using LLMs and Multimodal Brain Connectivity Analysis
- • [ELAMI] Pixel-FLAIR: Leveraging Anatomical Segmentation for Region-Specific Supervision in Retinal Foundational Vision-Language Models
- • [ELAMI] LLM-Based Differential Diagnosis of Neurodegenerative Diseases from MRI-Derived Brain Atrophy Reports
- • [ELAMI] Clinical Reliability in Multilingual Chest X-ray Report Generation
- • [ELAMI] PathLLaVA: Continuous Vision-Language Alignment for Bladder Cancer Pathology Report Generation
- • [ELAMI] Balancing Retrieved Evidence for 3D CT Report Generation
-
• [ELAMI] A Real-World Analysis of an AI Chest X-ray Reporting Assistant Focused on Factuality and Lines & Tubes
- Reynolds, Maxwell; Khandelwal, Ashish; Sharma, Harshita; Pérez-García, Fernando; Hansen, Michael; Colak, Ceylan; Mugu, Vamshi K.; Ouellette, Heather A.; Blasi, Marc E.; Nadkarni, Nishant; Swanstrom, Dana K.; Florers, Jennifer X.; Roering, Chris J.; Báez Suárez, Abraham; Cook, Cole J.; Kline, Timothy L.; Blezek, Daniel; Myers, Charles R.; Henckel, John D.; Mensing-Diggs, Amanda; Edwards, Matthew T.; Korfiatis, Panagiotis;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [ELAMI] FedPref: Federated Preference Learning for Structured Radiology Report Extraction
- • [ELAMI] Authority-Preserving Evaluation of Medical Vision-Language Assistants
- • [ELAMI] Evaluating Medical Report Generation on Real Clinical Data: A Case Study
- • [ELAMI] BioMAD: Biologically Guided Multi-Axis Delta Learning for Longitudinal Alzheimer’s Disease Classification
- • [ELAMI] LLM-HypSFCN: LLM-Guided Hyperbolic Structure-Function Coupling Network for Early Cognitive Assessment
- • [ELAMI] Sliding window-based local feature extraction for findings reports generation from longitudinal 3D CT volumes
- • [EMA] StrokeSeg2: Stroke Lesion Segmentation in Clinical Research Workflows
- • [EMA] Frequency-Hierarchical Active k-Space Sampling for Diagnostic MRI
- • [EMA] Test-Time Instance Selection for Improved Whole Slide Image Analysis
- • [EMA] Active few-shot segmentation by reinforcing data selection
- • [EMA] One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training
- • [EMA] Clinical Graph-Mediated Distillation for Unpaired MRI-to-CFI Hypertension Prediction
- • [EMA] Nine Dimensions Are Enough for Patch-Level Classification with Histopathology Foundation Model Embeddings
-
• [EMA] Efficient Fine-Tuning of Locally Deployable LLMs for Structured Data Extraction from Longitudinal Orthodontic Progress Notes
- Dumont, Paul; Buisson, Alexandre; Teixeira, Rodrigo; Aliaga, Aron; Yatabe, Marilia; Li, Tengfei; Dai, Runpeng; Zhu, Hongtu; Caleme, Eduardo; Barone, Selene; Miranda, Felicia; Mattos, Claudia Trindade; Kuo, I-Hsien; de Oliveira, Pedro José; Bianchi, Jonas; Cevidanes, Lucia H.;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [EMA] Boosting Generalizable Depth Estimation in Endoscopy by Mixture of Lightweight Experts and Intrinsic Image Alignment
- • [EMA] Multi-Teacher Contrastive Distillation for Edge-Efficient Pathology Foundation Models
- • [EMA] RadYOLO: Computationally Efficient 3D Object Detection and Segmentation in CT and MRI
- • [EMA] How Do Train-Time Pruning Dynamics and Pruning Schedules Affect Retinal Vessel Segmentation?
- • [EMA] MLSFP-CL: Label- and Compute-Efficient Contrastive Learning for Lung Nodule Classification in Small-Data Settings
- • [EMA] Edge2Prompt: Modality-Agnostic Model for Out-of-Distribution Liver Segmentation
- • [EMA] Low-Rank Adaptation for Efficient Contrast Specialization of 3D MRI Diffusion Models
- • [EMA] Unsupervised Adaptation of 3D CT Foundation Models for 3D CBCT Segmentation
- • [EMA] Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation
- • [EMA] Accelerating Chest X-ray Report Generation for Tuberculosis Screening in Indonesia: An Efficiency-Aware Benchmark of Quantized and Distilled Vision-Language Models
- • [EMA] Segmentation Without Full Logits: Fused Kernels for Memory-Efficient Many-Class Models
- • [EMA] BIEM: Bridging Implicit and Explicit Temporal Modeling for Surgical Phase Recognition
- • [EMA] When Efficiency Meets Fragility: Adversarial Vulnerability Shifts in Quantized Medical VLMs
- • [EMA] A Tiny Correction in the Right Place: Adapting a Fluorescence Super-Resolution Foundation Model
- • [EMA] MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification
- • [EMA] Towards Grounded GI Endoscopy VQA via Multi-Task Learning on Small VLMs
- • [EMA] How Many Labels Are Enough? ALDA: Active Learning Deployment Advisor for Medical Image Classification
- • [EMA] SGCA-UNet: Semantic-Geometric Coherence Attention U-Net for Joint Segmentation and Classification of Medical Images
- • [EMA] Guess where the pancreas is: scalable 3D foundation features with Finite quantisation, neighbourhood attention and red-black masking
- • [EMA] Segmentation Pre-training for Label-Efficient Lumbar Spine Degeneration Grading
- • [EMA] InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for 2D Medical Image Segmentation
- • [EMA] SecondOpinion: Anatomy-Aware Gated Reasoning for Efficient Medical Image Analysis
- • [EMA] Outlier-Suppressed Transformer for Efficient 3D Medical Image Segmentation
- • [EMERGE] Fully Automated CT-Based Differential Diagnosis of Bowel Wall Thickening
-
• [EMERGE] When Repository Labels Are Not Image-Level Truth: A Supervision Auditing Framework for Chest Radiograph AI
- Agudelo-Londoño, Yesika Alexandra; Pino-Román, Jhon Wilmer; Carrera Rodríguez, Brahian; Castañeda-Bedoya, José Miguel; Gómez-López, Juan Pablo; Puche-Sarmiento, Aura C.; D’Souza, Niharika S.; Osorio-Valencia, Juan Sebastian; Duque-Grajales, Jon E.; Suárez-Revelo, Jazmín Ximena; Vélez-Arango, Jorge Mario; Castrillón, Gabriel;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [EMERGE] FadeFormer: Content-Adaptive Graph Diffusion for Medical Image Classification
- • [EMERGE] Replication and Reproducibility Analysis of Breast Tumor Classification and Segmentation Benchmarks on the BreastDM Dataset
- • [EMERGE] Multi-Paradigm Fusion of XAI Methods for Chest X-ray Explanations
- • [EMERGE] Label- and Parameter-Efficient Lung Ultrasound Representation Learning via I-JEPA for Edge Diagnostics
- • [EMERGE] When Simple Wins: Lightweight CNN Encoders for Resource-Constrained Nucleus Segmentation
- • [EMERGE] Feature Extraction Strategies for Clinically Significant Prostate Cancer Detection on Biparametric MRI: A Systematic Ablation of the Local-Global MIL Framework
- • [EMERGE] Evaluating Concept-guided Visual Counterfactual Generation in Medical Imaging
- • [EMERGE] KneeDINO: Cross-Plane Attention Fusion for Multi-Label Knee Pathology Detection with Grounded LLM Explainability
- • [EMERGE] GraM-Diff: A Unified Graph–Mamba Diffusion Framework for EEG-Based Alzheimer’s Disease Data Generation and Diagnosis
- • [EMERGE] GPT-DBR: Decoding-Based Language-Model Regression for CT-Derived Lung-Function Estimation
- • [EMERGE] Linear and Non-Linear Dimensionality Reduction for Hyperspectral Overlapping Chromosome Segmentation
- • [EMERGE] Relational Learning of Temporal and Semantic Clinical Structured EHRs for Enhanced Patient Outcome Forecasting
- • [EMERGE] Annotation-Free Structured Delineation for Weakly Supervised PET Lesion Segmentation
- • [EMERGE] MedHyperGraph: EHR-Integrated Multimodal Hyperedges for Clinical VQA
- • [EMERGE] LocSAM3: Box-Supervised Adaptation of SAM3 for Text-Only Chest X-Ray Segmentation
- • [EMERGE] Label-Efficient Multimodal Microsleep Forecasting via Interpretable Disagreement-Driven Active Learning
- • [EMERGE] GF-BrainSR: Gated Frequency-Aware Selective State Space Model-Based Brain MRI Image Super-resolution
- • [EchoRisk] EchoMoVE: Multi-View Mixture-of-Experts Regression for Echocardiographic LVEF Estimation under Small-Cohort and Label-Imbalance Constraints
- • [EchoRisk] A Unified DINOv2-Based Framework for LVEF Estimation, GLS Dysfunction Classification, and Early Cardiotoxicity Prediction
- • [EchoRisk] CNN and ViT Backbone Fine-Tuning with Pseudo-Label Segmentations for the EchoRisk Challenge
- • [EchoRisk] Orthogonalising LVEF: Cyclic Consistency and Expert Cavity Supervision
- • [EchoRisk] MultiPhys-EF: Decorrelated Multi-Signal Fusion for LVEF Estimation in Cardiotoxicity Surveillance
- • [EchoRisk] One Encoder to Address All: Cardio-Oncology Assessment of Left Ventricular Ejection Fraction, Left Ventricular Dysfunction, and Early Cardiotoxicity in Echocardiography Cine Loops
- • [EchoRisk] Task-Specific Adaptation of Echocardiography Foundation Models for the EchoRisk-MICCAI Cardio-Oncology Challenge
- • [EchoRisk] Motion-Aware Multi-Stream Learning for Subclinical LV Dysfunction Detection from Echocardiography Videos
- • [EchoRisk] Multi-View Beat-Clip Probing of an Echocardiography Foundation Model for Cardio-Oncology
- • [EchoRisk] Foundation Model Fine-Tuning with Attention-based Multi-View Fusion for Multi-Task Cardiac Function Assessment
- • [EchoRisk] Deformation-Aware Expert Fusion for Echocardiographic Left Ventricular Dysfunction Assessment
- • [EchoRisk] Pretrained Echocardiography Video Models for LVEF Estimation and LV Dysfunction Classification
- • [EchoRisk] General vs. Echo-Specific Video Foundation Models for Echocardiographic Risk
- • [EchoRisk] EchoSense: Leveraging Foundation-Model Embeddings and Multiscale Temporal Modelling for Early Cardiotoxicity Prediction
- • [EndoLINA] EndoSplaTAM: Photorealistic Dense SLAM for Endoscopy Using Gaussian Splatting
- • [EndoLINA] More than Segmentation: Benchmarking SAM 3 for Segmentation, 3D Perception, and Reconstruction in Robotic Surgery
- • [EndoLINA] TRUE-Colon: Exposing a Consistent Transfer Asymmetry in Real-Time Polyp Detection
- • [EndoLINA] Topology-Constrained Vision-Language Sequence Modeling for Bronchoscopic Localization
- • [EndoLINA] SurgTriKG: Canonical Event Graphs for Training-Free Surgical Triplet Reasoning
- • [EndoLINA] CPR-Critic: Target-Label-Free Per-Frame Selection of Monocular Depth Estimators for Endoscopy
- • [EndoLINA] Adapting Generalizable Visual Geometry Models for Endoscopic 3D Reconstruction
- • [EndoLINA] ColScale3R: Parameter-Efficient Native-Scale Adaptation of Feed-Forward 3D Reconstruction for Colonoscopy
- • [EndoLINA] Towards Surgical World-Action Modeling: A Preliminary Joint Visual-Trajectory Forecasting for Surgical Motion Planning
- • [FAIMI-BRIDGE-EPIMI] Contrast-Induced Class Overlap as a Fairness Bottleneck in Dermatological AI: Evidence from HAM10000
- • [FAIMI-BRIDGE-EPIMI] Gradient Erasure and Contributory Injustice in Federated Medical Imaging AI
- • [FAIMI-BRIDGE-EPIMI] Investigating Sex and Ethnicity Bias in Deep Learning-based Echocardiography Image Segmentation
- • [FAIMI-BRIDGE-EPIMI] Hallucinations and constraints : Regulating surgical workflow recognition beyond accuracy
- • [FAIMI-BRIDGE-EPIMI] Look What the Probes Dragged In! Real-World Chest X-ray Shortcuts in MedCLIP
- • [FAIMI-BRIDGE-EPIMI] When Fairness Transfer Backfires: Dark-Skin Inversion in Dermatology Foundation Models and a Minimal In-Distribution Fix
- • [FAIMI-BRIDGE-EPIMI] Beyond Predictive Fairness: Quantifying Attribution Consistency Across Demographic Groups in Diabetic Retinopathy Screening
- • [FAIMI-BRIDGE-EPIMI] When Oracle Conditioning Misleads Deployment: Conditioning-Availability Bias in Echocardiographic Segmentation
- • [FAIMI-BRIDGE-EPIMI] Understanding Sources of Demographic Predictability in Brain MRI via Disentangling Anatomy and Contrast
- • [FAIMI-BRIDGE-EPIMI] On Evaluating Subgroup Discovery in Medical Image Classification
- • [FAIMI-BRIDGE-EPIMI] An Intersectional Fairness-Aware Framework for Alzheimer’s Disease Detection Using Multimodal Data
- • [FAIMI-BRIDGE-EPIMI] Marginal Coverage Hides a Reduced-Ejection-Fraction Reliability Gap: Severity-Conditional Conformal Intervals on Public Echocardiography
- • [FAIMI-BRIDGE-EPIMI] Intersectional Disentangling of Temporal and Acquisition Bias in Fetal Ultrasound
- • [FAIMI-BRIDGE-EPIMI] What is AI to Us: Exploring Patient Values in Integrating AI for Epilepsy Management
- • [FAIMI-BRIDGE-EPIMI] Foundational values for foundation models
- • [FAIMI-BRIDGE-EPIMI] Equal Accuracy, Unequal Agreement: Auditing Clinician–AI Agreement Fairness in Lung Nodule CT
- • [FAIMI-BRIDGE-EPIMI] Multiple Shortcut Pathways in Mammography-Based Breast Cancer Risk Prediction
- • [FAIMI-BRIDGE-EPIMI] Rethinking Explainability for Clinical Trust: A Task-Specific Communicative Layer
- • [FAIMI-BRIDGE-EPIMI] Futures Before Failures: Design Fictions for Anticipatory Fairness in Surgical AI
- • [FAIMI-BRIDGE-EPIMI] Counterfactual Stress Testing for Image Classification Models
- • [FAIMI-BRIDGE-EPIMI] Loss-Conditioned Utility-Fairness Boundary Modeling for Medical Imaging
- • [FAIMI-BRIDGE-EPIMI] From Fairness Findings to Fairness Claims: An Evidence Classification Scheme for Clinical AI
- • [FAIMI-BRIDGE-EPIMI] Subgroup performance analysis of adaptation strategies for chest X-ray foundation models
- • [FAIMI-BRIDGE-EPIMI] False Confidence: Automated Labels Confound Fairness Audits in Cervical Spine Segmentation
- • [FoundUS] Metric-Aware Semi-Supervised DINOv2 Ensembles for Unified Ultrasound Biometry
- • [FoundUS] MABA: Measurement-Aware Biometry Adaptation for Landmark-Based Ultrasound
- • [FoundUS] Attention-Gated U-Net with Heatmap Moment Coordinates for Multi-Organ Ultrasound Biometry
- • [FoundUS] USBiomWorld: Ultrasound Biometry World Model for Robust Landmark Measurement
- • [FoundUS] Semi-supervised DINOv3 Adaptation for Multi-domain Ultrasound Biometry
- • [FoundUS] SonoAdapt: Foundation Model Adaptation for Supervised Multi-Task Ultrasound Biometry
- • [FoundUS] TABS: Transfer-Aware Backbone Selection for Cross-Centre Ultrasound Biometry
- • [FoundUS] Baseline Method for Multi-Task Keypoint Localization in Fetal Ultrasound Imaging Baseline Implementation for Keypoint Localization Challenge 2026
- • [FoundUS] High-Resolution DINOv3-DSNT Landmark Regression for Multi-Organ Ultrasound Biometry
- • [FoundUS] Unified Coarse-to-Fine Landmark Localization for Multi-Domain Ultrasound Biometry
- • [FoundUS] Self-Supervised Domain Adaptation with DINOv2-HRNet for Multi-Task Ultrasound Landmark Detection
- • [FoundUS] A Unified Multi-Task Model for Ultrasound Biometry Landmark Detection under Extreme Label Scarcity
- • [FoundUS] Domain-Generalised Ultrasound Biometry via FiLM-Conditioned Multi-Task Landmark Detection with Progressive Semi-Supervised Learning
- • [FoundUS] Self-Assessing Anatomical World Model for Unified Multi-Domain Ultrasound Biometry
- • [FoundUS] A Unified Foundation-Model Framework with Semi-Supervised Consistency and Heatmap Ensembling for Nine-Task Ultrasound Biometry Regression
- • [FoundUS] A Unified Semi-Supervised Framework for Multi-Task Ultrasound Biometry Landmark Detection
- • [FoundUS] Towards Universal Ultrasound Biometry with Task-aware Foundation Models
- • [FoundUS] LandWorld: A Latent Predictive Foundation Model for Landmark-Based Ultrasound Biometry
- • [FoundUS] VSTA: A DINOv2-Based Unified Semi-Supervised Framework for Ultrasound Biometry
- • [FoundUS] UniUSB: Domain-Aware Adaptation of Vision Foundation Models for Unified Multi-Domain Ultrasound Biometry
- • [FoundUS] Encoder Capacity Is the Binding Constraint in Unified Multi-Task Ultrasound Landmark Detection
- • [FoundUS] Task-Conditioned Parameter-Efficient Adaptation for Robust Ultrasound Landmark Localization and Biometric Measurement
- • [FoundUS] CAMS: Coordinate-Aware Multi-task Semi-supervised Learning for Ultrasound Landmark Localization
- • [FoundUS] Multi-Task Landmark Detection for Fetal and Cardiac Ultrasound Biometry under Label Scarcity
- • [FoundUS] Stable Landmark Identity and Unlabeled Adaptation: A ConvNeXt Framework for FoundUS 2026
- • [FoundUS] SonoDiNoV2: Geometry-Aware, Pseudo-Label Guided Multi-Task Ultrasound Model
- • [FoundUS] Multi-Task Ultrasound Biometry Landmark Detection
- • [FoundUS] Hierarchical Ensembles of Complementary Landmark Detectors for Multi-Task Ultrasound Biometry
- • [FoundUS] PULSE-FM: A Foundation Model for Ultrasound Biometry with Task Adaptation and Progressive Landmark Refinement
- • [FoundUS] A Single Unified DSNT Model with Protocol-Calibrated Readout for Generalizable Multi-Task Ultrasound Biometry
- • [FoundUS] PULSE: Pseudo-labelling of Ultrasound by Local-to-Semantic Expansion for Generalisable Biometry
- • [GRAIL] GraphSVR: q-Space–Aware Graph-Based Slice-to-Volume Registration for Diffusion MRI
- • [GRAIL] Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction
- • [GRAIL] Diffusion-based Perturbation Modeling for Unsupervised Detection of Sulcal Pattern Alterations
- • [GRAIL] FBN-Bench: Do Graph-Based Deep Learning Models Improve Functional Brain Network Classification?
- • [GRAIL] Imaging the Topology of Dynamic Brain Connectivity
- • [GRAIL] TumorGraphs: Patient-Level Fusion of Multi-WSI Histopathology
- • [GRAIL] Temporally Consistent Graph Extraction and Matching for Longitudinal Angiographic Images
- • [GRAIL] Topological Deep Learning on Graphs for Arrhythmia Risk Prediction From Images
- • [GRAIL] A Continuous Optimization Approach for Graph Cuts-based Phase Unwrapping
- • [GRAIL] MetaCBT: A Multi-Layer Connectional Brain Template for Reproducible Population-Level Biomarker Discovery
- • [HAIC26] AI-assisted labeling and its pitfalls: A case study in Electron Microscopy segmentation
- • [HAIC26] Adapt While You Annotate: The Missing Complement to Interactive Segmentation
- • [HAIC26] Accounting for Over-Reliance in AI-Assisted Performance Studies
- • [HAIC26] Characterizing Global and Local Model Behavior in Interactive Segmentation
- • [HAIC26] Why AI Fails to Influence Admission Decisions: Evidence from a Case Study
- • [HAIC26] Standardizing MRI Patient Setup with Real-Time Camera Guidance and Worklist-Driven Scan Intent
- • [HAIC26] Human Checkpoints in Automated Speech-to-Report Generation: Radiologist Correction for CEUS LI-RADS Categorization
- • [HAIC26] Verbalized Findings as the Interface for Near-Term Human–AI Collaboration in Radiology: A Clinical Perspective on LLM-Assisted Diagnosis
- • [HAIC26] Towards Interpretable AI Second Opinions: Foundation Model Heatmaps in Radiology
- • [HAIC26] Beyond One-Shot Interaction: Framing Pathology Human–AI Collaboration via Workflow Evidence
- • [HAIC26] Rethinking Ultrasound Datasets via Clinical Human–AI Collaboration Tiers
-
• [HAIC26] It’s Time to Talk Human-Centered Research at MICCAI
- Cho, Sue Min; Gomez, Catalina; Breininger, Katharina; Creighton, Francis; Guo, Xiaoqing; Ho, Dean; Ishii, Masaru; Jannin, Pierre; Kersten, Marta; Kim, Seong Tae; Navab, Nassir; Ouyang, Cheng; Wu, Shandong; Yi, Paul; Zuluaga, Maria A.; Unberath, Mathias;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [HAIC26] A3F: Anatomy-Aware Actionable Feedback for Fetal Ultrasound
- • [HAIC26] Toward Agentic Echocardiography: Reinforcement Learning with Foundation-Model Similarity Rewards in a CT-Derived Simulation
- • [HAIC26] Learning to Defer with Guidance on Real World Medical Data
- • [HAIC26] IBS: Interactive Batch Selection for Medical Image Segmentation
- • [HAIC26] IMVS: Interactive Medical Volume Segmentation with Test-Time Adaptation - A New Method for Annotating Radiology Datasets
- • [HAIC26] Fetal-CARE: Collaborative Annotation with Reviewer-Stratified Expertise for Fetal Ultrasound Standard Plane Classification
- • [HEADLINE] Entity-Aware Head CT Report Generation via Classification-Derived Label Priors
- • [HEADLINE] FiReGen: Findings-Aware Retrieval and Reinforcement-Tuned Generation of Free-Text Head CT Radiology Reports
- • [HEADLINE] Low-Rank Adaptation of a 3B Vision-Language Model for Head-CT Report Generation: HEADLINE 2026
- • [HEADLINE] E-Head: Efficient Head CT Report Generation via Multi-Resolution Series Integration and Two-Stage Parameter-Efficient Fine-Tuning
- • [HEADLINE] CIRCA: Maximising Per-Slice Detail for Head-CT Report Generation with a Windowed-RGB and Split-Slab Bone-Projection Representation for the HEADLINE Challenge
- • [HEADLINE] Head CT Report Generation from Subsampled Slices with Candidate Selection
- • [HEADLINE] Finding-Aware Contrastive Re-Alignment for Head CT Report Generation
- • [HECKTOR] HERMES: A Hybrid Ensemble for Head-and-Neck Tumor Segmentation, TN Staging, and Recurrence-Free Survival on PET/CT
- • [HECKTOR] Modernizing nnU-Net with Convolutional SwiGLU for Segmentation, Staging, and Prognosis in HECKTOR 2026
- • [HECKTOR] Deep Learning-Based Segmentation and Feature-Based Clinical Prediction for Head and Neck Cancer
- • [HECKTOR] Unified vs modular methods for head-neck tumor and lymph node segmentation, staging, and survival prediction
- • [HECKTOR] Automated Head and Neck Cancer Characterization from PET/CT: A Framework for Segmentation, TN Staging, and Recurrence-Free Survival Prediction
- • [HECKTOR] Wide-Field PET/CT Segmentation, Local Refinement, and Clinical-Variable Models for HECKTOR 2026
- • [HECKTOR] Efficient Multi-Task Framework for Head and Neck Segmentation, Staging, and Prognosis
- • [HECKTOR] A Segmentation-Guided Framework for TN Staging and Recurrence-Free Survival Prediction in HECKTOR 2026
- • [HECKTOR] A Late-Fusion Framework for Joint Tumor Segmentation, Staging, and Recurrence Prediction in Head and Neck Cancer
- • [HECKTOR] BRACHIO: Broad Representations Across Centres for Head-and-neck Imaging Oncology
- • [HECKTOR] From Tumor Segmentation to Clinical Prediction: A PET/CT Pipeline for Head and Neck Cancer
- • [HECKTOR] Predicted Masks Throughout: A Cross-Center Generalizable Pipeline for Joint Head and Neck Tumor Segmentation, Staging, and Prognosis
- • [HECKTOR] A Dual-Branch Fusion Pipeline for Head and Neck Tumor Segmentation, TN Staging, and Recurrence-Free Survival Prediction: HECKTOR 2026
- • [HECKTOR] JOTAC-HN: Joint Outcome and TN Assessment Cascade for Head and Neck Cancers
- • [HECKTOR] Geometry Meets Metabolism: Interpretable Segmentation, Staging, and Prognosis in Head and Neck PET/CT
- • [HECKTOR] GASP: Multimodal Geometry-Aware Segmentation, Staging, and Prognostication of Head and Neck Cancer
- • [HemaRAI] Can You Trust Frozen Hematology Foundation Models under Acquisition Shift?
- • [HemaRAI] Task-guided Hierarchical Multi-stain CycleGAN with Contrastive Learning for Robust White Blood Cell Classification
- • [HemaRAI] MaLDAM: Masked Localized Domain Adaptation for Malaria Detection in Low-Cost Microscopic Images
- • [HemaRAI] Comparing Centralized and Federated Learning for ECG-Based Chagas Disease Detection
- • [HemaRAI] A Novel Semi-Supervised Approach for Red Blood Cell Shape Analysis in Flow
- • [ISIC] Assessing Multimodal Chronic Wound Embeddings with Expert Triplet Agreement
- • [ISIC] Dual-Penalty Conformal-Aware Loss for Reliable Skin Lesion Classification Under Class Imbalance
- • [ISIC] Automated Skin Lesion Detection in Total Body Photography: A Multi-Architecture Benchmark
- • [ISIC] DermaNet: Flexible-View Fusion for Dermoscopic–Clinical Skin Lesion Classification
- • [ISIC] LUTSeg: A Longitudinal Multi-Expert Dataset for Ulcer Tissue Segmentation
- • [ISIC] Taxonomy-Guided Vision–Language Representation Learning for Hierarchical Skin Disease Classification
- • [ISIC] Multi-Dataset Diagnostic Utility of Clinical Visual Concepts in AI Systems for Dermatology
- • [ISLES] A Metadata-Informed Two-Stage nnU-Net Cascade for Ischemic Stroke Lesion Segmentation
- • [ISLES] SADL: A Size-Adaptive Decision Layer for Chronic Stroke Lesion Segmentation in ISLES 2026
- • [ISLES] Ladle-ResEncL with Lesion-Size-Weighted Learning for Ischemic Stroke Lesion Segmentation
- • [ISLES] From Baseline to Bilateral Asymmetry: A Systematic nnU-Net Comparison for Ischemic Stroke Lesion Segmentation in ISLES’26
- • [ISLES] Adaptive Post-Processing Drives Instance-Level Detection in Stroke Lesion Segmentation
- • [ISLES] Residual-Encoder nnU-Net with Small-Component Filtering for Multi-Site Stroke Lesion Segmentation in T1-weighted MRI
- • [ISLES] Investigating Small-Lesion Segmentation Failures in Acute Ischemic Stroke: An nnU-Net Baseline Analysis for ISLES'26
- • [ISLES] MWCA-Net: Metadata-Conditioned 3D UNet for ISLES 2026 Stroke Segmentation
- • [ISLES] T1w MRI Stroke Lesion Segmentation with Optimized Preprocessing and Residual Encoder nnU-Net
- • [ISLES] Deconver for Stroke Lesion Segmentation
- • [ISLES] Bottleneck-Mamba 3D U-Net Baseline for Lesion Segmentation in ISLES’26 Ischemic Stroke: Limited by Precision in Segmenting Small and Multifocal Lesions
- • [ISLES] Ranking-aware model selection for stroke lesion segmentation
- • [ISLES] LightMedSeg-ISLES: Stroke Lesion Segmentation with 81× Fewer Parameters than nnU-Net
- • [ISLES] Native-Space 3D CarveMix for Multi-Site T1w Stroke Segmentation
- • [ISLES] Dual-Family Ensembling and Failure-Mode Analysis for Ischemic Stroke Lesion Segmentation in Single-Sequence T1w MRI
- • [ISLES] Atlas-Centric Multi-Center Ischemic Stroke Lesion Segmentation with MedNeXt++
- • [ISLES] Evaluating Pipeline Design Choices for Chronic Stroke Lesion Segmentation in T1-Weighted MRI
- • [ISLES] Voxels or Millimetres? A Controlled Comparison of Lesion-Size Filtering for Native-Space Stroke Segmentation
- • [ISLES] Residual-Encoder nnU-Net for Multi-Phase Ischemic Stroke Lesion Segmentation in Native-Space T1-Weighted MRI
- • [LISA] A Dual-Stream Regulated Reconstruction and Segmentation Network with Hierarchical Artifact-Prior Modeling for Ultra-Low-Field Pediatric Neuroimaging
- • [LISA] A Unified Masked Autoencoder Framework for Quality Assessment, Image Restoration, and Multi-Structure Segmentation in Low-Field Pediatric Brain MRI
- • [LISA] Pretrained and Self-Configuring Ensembles for Pediatric Ultra-Low-Field Brain MRI Analysis
- • [LISA] Slice-Based 2D Transfer Learning Outperforms 3D-From-Scratch for Quality Assessment of Ultra-Low-Field Neonatal MRI
- • [LISA] Automated Artifact Quality Control for Pediatric Low-Field MRI via Plane-Aware CNNs and BrainFM Feature-Pyramid Expert Merging
- • [LISA] A Modular Multi-Model Framework for Multi-Structure Segmentation of Ultra-Low-Field Pediatric Brain MRI
- • [LISA] Diverse-Loss Backbone Ensembling for Multi-Label Artifact Quality Assessment of Ultra-Low-Field Pediatric Brain MRI
- • [LISA] Dual-Annotation Assisted Boundary-Aware Segmentation for Ultra-Low-Field Pediatric Brain MRI
- • [LISA] Generalized Prior-Conditioned MRI Segmentation for Ultra-Low-Field Pediatric Brain Structure Segmentation
- • [LISA] Rigor over Novelty in Ultra-Low-Field Pediatric Brain MRI: Quality Control and Subcortical Segmentation for the LISA Challenge 2026
- • [LISA] Ensembled Laterality-Aware Residual nnU-Net for Low-Field Pediatric Brain MRI Segmentation
- • [LISA] A 2.5D Ordinal Quality Assessment and Metadata-Preserving Residual Restoration Framework for Ultra-Low-Field Pediatric Brain MRI
- • [LISA] Quality Assessment, Enhancement, and Subcortical Segmentation of Ultra-Low-Field Pediatric Brain MRI: The LISA 2026 Challenge
- • [LISA] Asymmetric Paired-Annotation Learning for Multi-Structure ULF Pediatric Brain MRI Segmentation
- • [LISA] Enhancing Neuroanatomical Segmentation and Quality Assurance in Pediatric Ultra-Low-Field MRI
- • [LISA] Deep Learning Models for Automated Quality Assessment and Artifact Reduction in Ultra-Low-Field Pediatric Brain MRI
- • [LISA] Axis-aware Image Artifact Evaluation and Asymmetry-aware Multi-Label Segmentation of Subcortical Structures in Low-Resolution Pediatric Brain MRI
- • [LISA] Physics-Aware k-Space Artifact Simulation for Quality Assessment of Ultra-Low-Field Pediatric Brain MRI
- • [LISA] LoFi RADIO: A Distilled In-Domain Backbone Applied for Artifact-Severity Grading of Ultra-Low-Field Neonatal Brain MRI
- • [LISA] Overcoming Low Signal and Scarce Data: Quality Assessment, Enhancement, and Segmentation of Ultra-Low-Field Pediatric Brain MRI
- • [LISA] Atlas-Guided Local Expert Fusion for Pediatric Ultra-Low-Field Brain MRI Segmentation
- • [MAMA-SYNTH] MAMA-FLUX.2: Image-to-Image Synthesis of Post-Contrast Breast DCE-MRI for the MAMA-SYNTH Challenge
- • [MAMA-SYNTH] MIRAGE: Multi-scale Lesion-Informed Representation with Auxiliary Guidance for MRI Contrast Enhancement
- • [MAMA-SYNTH] Anguinus Sculpturae: Compositional Synthesis of Peak-Enhancement Breast DCE-MRI Scans
- • [MAMA-SYNTH] DARE: Dilated Anatomy-Anchored Residual Enhancement for Virtual Contrast Synthesis in Breast DCE-MRI
- • [MAMA-SYNTH] Pre- to Post-Contrast Synthesis of Breast DCE-MRI using Latent Bridge Matching
- • [MAMA-SYNTH] Two-Stage Enhancement-Field Synthesis of Contrast-Enhanced Breast MRI from Pre-Contrast Slices
- • [MAMA-SYNTH] Tumor-Aware Residual nnU-Net for Virtual Peak-Enhancement Breast DCE-MRI Synthesis from a Single Pre-Contrast Slice
- • [MAMA-SYNTH] Lesion-Aware Virtual Contrast-Enhancement in Breast MRI Using CycleGAN
- • [MAMA-SYNTH] Where and How Much: Enhancement-Decomposed Flow Matching for Virtual Contrast-Enhanced Breast MRI
- • [MAMA-SYNTH] Supervised Virtual Contrast Enhancement in Breast MRI with Multi-Domain Losses and Lesion-Aware Decoding
- • [MAMA-SYNTH] When Regression Beats Generation: Virtual Contrast-Enhanced Breast MRI and What Its Metrics Reward
- • [MAMA-SYNTH] Tumor-Aware Conditional Pix2PixHD with Per-Image Normalization for Virtual Contrast Enhancement in Breast MRI
- • [MAMA-SYNTH] Predictive Enhancement Calibration for Latent Breast MRI Virtual Contrast Enhancement
-
• [METIS] Multidisciplinary Evaluation and Translation in Imaging and Surgery (METIS) 2026: Bridging Clinical and Computational Communities for the Next Generation of Medical Imaging AI
- Navas, Alin; Astaraki, Mehdi; Bazay, Fatima Ez-Zahraa; Chiumento, Francesco; Kachole, Sanket; Lee, Jongwoon; Oladejo, Ezekiel Ayodeji; Soares, Antonio S.; Rudie, Jeffrey D.; Calabrese, Evan; Aboian, Mariam S.; Safdar, Aon; Saadeldin, Mohamed; Healy, Nuala A.; Ochoa-Ruiz, Gilberto; Ali, Sharib; Yilmaz, Bulent; Papież, Bartłomiej W.; Bakas, Spyridon; Curran, Kathleen M.;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MI4MedFM] GRD-DCA: Region-Conditioned Refinement for Grounded Radiology Report Generation
- • [MI4MedFM] AUC Is Not Enough: Compression Can Preserve Classifier Performance While Altering Interpretable Structure in Pathology Embeddings
- • [MI4MedFM] Which Reliability Signal to Trust? Output vs. Representation Space Uncertainty Under Distribution Shift in Pathology Foundation Models
- • [MI4MedFM] Leveraging Projected Residual Stream Decomposition for Mechanistic Probing and Parameter-Efficient Repair of Biomedical CLIPs
- • [MI4MedFM] Self-Supervised Vision Transformers for CBCT-Based Detection of Temporomandibular Joint Osteoarthritis
- • [MI4MedFM] Evaluating the potential and limitations of MedSAM for acute stroke lesion segmentation
- • [MI4MedFM] Counterfactual Activation Patching of Pleural-Effusion Boundary Failures in MedSAM
- • [MI4MedFM] Label-Free Parkinson’s Disease Screening from Face and Voice through Mechanistic Interpretability
- • [MI4MedFM] LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation
- • [MI4MedFM] Reading Between the Lesions: Auditing Whether Multimodal Dermatology Classifiers Actually Use Clinical Text
- • [MI4MedFM] The Metric, Not the Model: Anatomy Confounds Attention Faithfulness in Coronary Calcium
- • [MI4MedFM] Interpretable Missense Variant Effect Prediction via Sparse Feature Changes in ESM-2
- • [MI4MedFM] PATH-DISSECT: Interpreting Concept Representation and Classifier Reliance in Pathology Foundation Models with Sparse Autoencoders
- • [MI4MedFM] Do Medical Vision Models Reason About Anatomy? Probing the Spatial Inductive Biases of Learned Visual Representations
- • [MIART] Supporting Clinical Trial Quality Assurance of Organ-at-Risk Contours with Image-Conditioned Diffusion Models
- • [MIART] WING: A Window-Prior-Based Generative Network with Gated Inception for Cross-Modality CT Synthesis
- • [MIART] 4D Pencil Beam Treatment Plan with Conditional Weight Predictions
- • [MIART] More Comprehensive and Reliable Deep Learning Normal Tissue Complication Probability Models for Head and Neck Cancer Patients
- • [MIART] PR3DICTR: a 3D Image-Based Deep Learning Prediction Modelling Framework and its Use in Radiotherapy
- • [MIART] Dynamic Modeling of Brain Metastasis Response with Multitask Temporal Learning
- • [MIART] SynthRCT: Scalable Conditional Deformation Synthesis for Synthetic Repeat CT Generation
- • [MIART] Heterogeneous IMRT and VMAT Dose Calculation using Deep Learning with Beam Path Reconstruction and PTV Information
- • [MIART] Recognizing Dosimetrically Irrelevant Edits of Auto-Segmentations in Head and Neck Organs of Interest
- • [MIART] Can we trust synthetic CT algorithms? Uncertainty-aware evaluation of CBCT to CT synthesis for adaptive proton therapy
- • [MIART] DoMa-Seg: Dose Map Guidance for Medical Image Segmentation in Head and Neck Radiotherapy
- • [MIART] Which Edits Matter? Simulating Realistic Local Corrections to Organ-of-Interest DL Segmentation and Predicting Dosimetric Impact
- • [MIART] Motion-Consistent Memory for Foundation Model-Based Tumor Tracking in MR-guided radiotherapy
- • [MIART] A Differentiable Gaussian Mixture Model-based Scorecard for Cohort-Aware Radiotherapy Plan Evaluation and Optimization
- • [MIART] Generalizing Monte Carlo dose reconstruction beyond the training anatomy using conditional diffusion models
- • [MIART] Cross-Modal Spatial Gating of Planning-MRI Priors for Longitudinal CBCT-to-CT Synthesis
- • [MIART] Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis
- • [MIART] EPC-3D-Diff: Equivariant Physics Consistent Conditional 3D Latent Diffusion for CBCT to CT Synthesis
- • [MIART] An Uncertainty-Guided Multi-Scale SwinUNETR Framework for 3D Larynx Segmentation in CT
- • [MIART] MRI-to-Synthetic CT for Intracranial Stereotactic Radiotherapy: a Comparative Study of Deep Learning Architectures with Focus on Bone Fidelity
- • [MIART] Mamba-driven MRI-to-CT Synthesis for MRI-only Radiotherapy Planning
- • [MIART] Parameter-Efficient pretrained-CT-to-MRI Transfer for Rectal Cancer Segmentation: Performance-Calibration Trade-offs
- • [MIART] CBCT Segmentation in Head and Neck ART: A Longitudinal Deep Learning Approach
- • [MIART] Uncertainty-Aware Out-of-Field Dose Prediction in External Beam Radiotherapy
- • [MIART] Patient-Informed XCAT Modelling of Free Breathing and Deep-Inspiration Breath Hold Anatomy: A Feasibility Study
- • [MIART] Mammo-LIFE: Longitudinal Mammographic Imaging and Clinical Feature Enrichment for Post-Radiotherapy Outcome Prediction
- • [MIART] Is Deformable Image Registration Ready for Brain Metastasis Reirradiation Dose Accumulation? A Longitudinal MRI Benchmark of Registration Accuracy
- • [MIRASOL] Gaussian Regularized Spatial Masking for Enhanced Malaria Blood Smear Augmentation in Resource-constrained Settings
- • [MIRASOL] Trustworthy TB Screening: Backdoor Vulnerability and Lightweight Defense in Chest X-Ray AI
- • [MIRASOL] ExBale: Quantitative Evaluation of Explainability Alignment in Ovarian Ultrasound Imaging
- • [MIRASOL] Clean AUC Is Not Enough: Architecture-Specific Failure Modes of Tuberculosis Classifiers under Digitisation Artifacts
-
• [MIRASOL] MORPHA: Morphology-Constrained Training and the Limits of Cross-Acquisition Transfer in Low-Resource Malaria Microscopy
- Igwezeke, Favour Okechukwu; Ugwuishiwu, Chikodili Helen; Anozie, Ekenechukwu Lilian; Emesiani, Joseph Uzochukwu; Agada, Samuel Ifebuche; Kama, Mary Ofuru; Anazodo, Udunna C.; Zhang, Dong; Raymond, Confidence; Iorumbur, Aondona Moses; Emegoakor, Adaobi Chiazor;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MIRASOL] Towards CPU-Deployable nnU-Net: Training-Free Sensitivity-Guided Compression Across Clinical Domains
- • [MIRASOL] Toward a minimum viable MRI protocol for glioma segmentation in resource-constrained settings
- • [MIRASOL] Efficient Explainable AI for Multi-Label Chest Disease Detection in Resource-Constrained Settings via Knowledge Distillation and Quantization
- • [MIRASOL] Beyond Dice: Evaluating Reliability and Robustness in Breast Ultrasound Lesion Segmentation Under Progressive Speckle Corruption
- • [MIRASOL] Uncertainty-Based Referral for Selective Chest X-Ray Classification
- • [MIRASOL] Investigating White Blood Cells as a Source of False-Positive Malaria Parasite Detection in African Blood-Smear Images
- • [MIRASOL] Segmentation-Guided Inpainting and Imbalance-Aware Learning for Robust Ovarian Tumor Classification in Ultrasound
- • [MIRASOL] CORTEX: Deep Reinforcement Learning with Pulse-Sequence Computation for Resource-Efficient MRI Protocol Adaptation
- • [MIRASOL] Compact Radiomics-Guided FiLM Conditioning for Ultrasound-to-MRI Translation
- • [MIRASOL] Frugal and Agentic AI for Medical Imaging in Resource-Constrained Settings: A Sustainable Framework
- • [MIRASOL] A Low-Cost AI Stethoscope for Resource-Constrained Heart Murmur Screening
- • [MIRASOL] Hierarchical Task Framing for Prevention-Oriented Cervical Lesion Detection Using Nigerian Colposcopy Images
- • [MIRASOL] TRIDENT: Safety-Gated, On-Device Triage for Paediatric Teledermatology on Pigmented Skin
- • [MIRASOL] Domain-Specific Augmentation and Uncertainty Quantification for Robust Breast Ultrasound Lesion Segmentation and Classification
- • [MIRASOL] Fairness and Cross-Regional Generalizability of State-of-the-Art Glioma Segmentation Models: Evaluation Across African and Global Cohorts
- • [MIRASOL] Sensitivity-Optimized Tuberculosis Triage Using Nigerian Chest X-Rays
- • [MIRASOL] Discrimination Is Not Enough: Calibration-Aware Multimodal Classification of Benign and Malignant Lesions in Contrast-Enhanced Spectral Mammography
-
• [MIRASOL] Towards the Development of a Clinical Safety Acceptance Rule for Low-Field MRI using Hybridized Uncertainty-Aware Autoencoders
- Funperefagha, Mberekpe Emmanuel; Jimoh, Nafisa Opemi; Tijjani, Usman; Oyelami, Oyewole; Okegbemi, Joshua Taiwo; Usman, Hafsat Muhammed; Obe, Olumide Olayinka; Thisleton, William; Raymond, Confidence; Iorumbur, Aondona Moses; Anazodo, Udunna C.; Adewole, Maruf; Adebayo, Adegboyega;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MIRASOL] Patient-Paired Anatomical Consistency Learning for Cross-View Echocardiographic Segmentation
-
• [MIRASOL] Large-Scale Pretraining for Improving Deep Learning-Based Geometric Distortion Correction of Diffusion-Weighted Imaging
- Khanal, Saroj; Yadav, Yashawant Kumar; Bhattarai, Kritam; Neupane, Jeevan; Subedi, Shristi; Gwachha, Saship; Tiwari, Manish Kumar; Zhang, Dong; Raymond, Confidence; Iorumbur, Aondona Moses; Anazodo, Udunna C.; Khanal, Bishesh; Shakya, Mahesh; Shrestha, Pralhad Kumar;
- [PDF] [Paper Information and Reviews] [bibtex]
-
• [MIRASOL] FLAIR Dependence Confounds Cross-Modal Consistency for SegResNet Reliability Estimation on BRaTS-Africa
- Mfetane, Ofile Seneo; Sepora, Tshegofatso Olorato; Moerane, Aobakwe; Kayuna, Matthew; Oats, Unotjari; Lungowe, Sililo; Makgasane, Magnus Tiiso; Sebina, Seipone Talama; Manyanda, Letso Jessica; Chibuta, Peter; Hassan, Maryam Olaitan; Anazodo, Udunna C.; Iorumbur, Aondona Moses; Raymond, Confidence; Sidume, Freedmore;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MIRASOL] Representation Learning from Superpixels: Lightweight CNN Encoders Under Data Scarcity
- • [MIRASOL] Physics-Informed Deep Learning for Accelerated Open-Source Low-Field MRI Reconstruction
- • [MIRASOL] Characterizing Domain Shift in Glioma Segmentation Between Global North and African MRI Datasets
-
• [MIRASOL] False-Positive Reduction in Automated Malaria Parasite Detection from African Blood Smears: A Falsification-to-Mitigation Study
- Oghenewoakpo, Supreme Onowoakpo; Supreme, Mercy Ajoke; Kukudabi, Seth Kwabena Kyei; Yakubu, Kanyiri Ahmed; Yinsuu, Gideon; Buernorkie Agbugblah, Doreen; Beckley, Oserebameh Augustine; Agwu, Mary; Zhang, Dong; Raymond, Confidence; Iorumbur, Aondona Moses; Mumuni, Abdul Nashirudeen; Opara, Chidera; Adewole, Maruf; Tigbee, Isaac;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MIRASOL] Silent Failures in Degraded Chest X-Rays: Benchmarking Uncertainty Methods for Pneumonia Triage in Resource-Constrained Settings
- • [MIRASOL] From Binary Labels to Stage-Aware Bounding Boxes: Evaluating Annotation Depth in Malaria Microscopy
- • [MIRASOL] Token Mixer Placement Matters: A Systematic Encoder–Decoder Ablation Study of Mamba for Brain Tumour Segmentation on BraTS-Africa
- • [MIRASOL] NIMARC-MRI: Abdominal HASTE Dataset and a Baseline U-Net Exposing the Synthetic-to-Real Gap in Low-Resource Motion Correction
- • [MIRASOL] MYRA: Multi-domain Hybrid MRI Representation Architecture for Self-Supervised Low-Field MRI
- • [MIRASOL] Does Smear Preparation Type Constitute a Domain Boundary? Within-Domain Baselines and a Transfer Protocol for Malaria Microscopy
- • [MIRASOL] Prevention-Oriented Cervical Cancer Triage Using a Nigerian AI Screening Dataset
- • [MIRASOL] Benchmarking Explainable AI for Brain Tumour Segmentation and Classification in African MRI
- • [MIRASOL] Local Audit Certification of Transferred Medical Imaging Models in Resource-Constrained Settings
- • [MIRASOL] Eyes on diet: a low-resource framework connecting diabetic retinopathy screening to regional nutritional guidance
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• [MIRASOL] Breast Lesion Detection from Community-Acquired POCUS Images: A Framework Proposal Based on Transfer Learning for Improved Screening in Africa
- Gbolahan, Temitayo Ismail A.; Chabi, Wahabou K. Taba; Hounton, Johannes; Cocouvi, Alexandre; Missihoun, Jonathan Suru; Hovozounkou, Rodrigue; Legbassi, Gildas Sèyigbénan; Minaba, Sêgnimaké Tatiana Carine; Musah, Toufiq; Kalaiwo, Chinasa; Anazodo, Udunna C.; Raymond, Confidence; Iorumbur, Aondona Moses; Bankole, Nourou Dine Adeniran;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MIRASOL] WebMRIQC: A Web-Based Implementation of MRIQC for Accessible MRI Image Quality Assessment in Resource-Constrained Settings
- • [MIRASOL] Beyond Real-Valued MRI Features: Complex Broad Learning for Early Alzheimer’s Disease Diagnosis
- • [MIRASOL] Efficient Diffusion-Based Synthetic Augmentation with Automatic OOD-Driven Filtering for Long-Tailed Skin Lesion Classification in Resource-Constrained Settings
- • [MIRASOL] Where Does the Discrepancy Come From? Probing Healthy vs. Tumor fMRI with Convolutional and Statistical Lenses
- • [MIRASOL] Soft Temporal Scoring Using a Foundation Model: Optimal Frame Selection for Improved ONSD Measurement in Ultrasound Videos
- • [MIRASOL] TRIUNE-Net: Harmonizing Scale, Shape, and Efficiency in Pancreatic Tumor Segmentation
- • [MIRASOL] Leveraging Cardiac Imaging to Improve ECG-Based Detection of Chagas Disease in Resource-Constrained Settings
- • [MIRASOL] User-Friendly AI Software for Automated Quantitative CMR Reporting on Low-Cost, Energy-Efficient Devices
- • [MIRASOL] Partial Information Decomposition as a Multi-Contrast 3D MRI Selection Strategy for Resource-Constrained Deep Neural Network Training in Brain Tumor Segmentation
- • [MIRASOL] A Sensitivity-Gated Cascade for Compute-Efficient Spinal Lesion Detection in Resource-Constrained Settings
- • [MIRASOL] WaRA: Wavelet Low-Rank Adaptation for Medical Image Classification
- • [MIRASOL] Disease Burden over Skin Tone: Decomposing the Dermatology-AI Generalization Gap
- • [MIRASOL] SKDrepaData: A Multisite West African Blood Smear Dataset for Automated Sickle Cell Disease Detection and Classification
- • [MIRASOL] RAINet: Multi-Scale Involutional Model for Resource-Constrained Medical Image Classification Across Modalities
- • [MIRASOL] Dataset-Free Dermoscopic Hair Removal
- • [MIRASOL] LDCT-to-SDCT as a Bridge Problem: Single-Step Residual Endpoint Flow Matching for Real-Time Denoising
- • [MIRASOL] Effect of Pretrained Initialisation and Component-Wise Tuning on Lightweight VLMs for Ultrasound Report Generation
- • [MIRASOL] Label-Free Foundational Model Selection for Medical Image Classification under Distribution Shift via Pseudo Label Discrepancy
- • [MIRASOL] MR-DiffRecon: Efficient All-in-One MRI Reconstruction with Multi-Scale Alignment and Implicit Prompting
- • [MIRASOL] Contrastive Radiomics-to-Image Alignment for Cross-Modal Mammographic Mass Retrieval
- • [MIRASOL] Edge Deployment of Multimodal Clinical AI on Low-Cost Hardware for Resource-Constrained Settings
- • [MIRASOL] Beyond validation loss: Clinically-tailored metrics for hyperparameter optimization improve a model’s clinical performance
- • [MIRASOL] CoSWA-YOLOv12: Scale-Invariant Tiny Object Detection and Segmentation of Malaria Parasites
- • [MIRASOL] AutoFLIM: Joint Optimization of Architecture, Markers, and Hyperparameters for Efficient Medical Image Segmentation
- • [MIRASOL] Deployment-Oriented Benchmarking of Optimized Deep Learning Models for Real-Time Fetal Plane Classification on Mobile Devices
- • [MIRASOL] An Open-Source Workflow for Automated 3D Spine Reconstruction from Tracked Ultrasound: A Pilot Study in Senegal
- • [MISO] DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction
- • [MISO] From Cross-Section to Cross-Omics: Conditional Cell Nucleus Image Editing in Spatial Transcriptomics
- • [MISO] Identifiable Counterfactual Control Defines Glioma Drivers: A Multi-Scale Causal Framework that Abstains Off-Support
- • [MISO] Towards Virtual Biopsy in Ovarian Cancer Through MRI-WSI Registration
- • [MISO] Leveraging Cell-level Spatial Transcriptomics as Weak Supervision for Nuclei Classification
- • [MISO] Iterative Gamma Normalization for Inter-Sample Integration of Multiplexed Tissue Images
- • [MISO] IsoMobil: Resolving Molecular Ambiguity in Mass Spectrometry-based Spatial Omics Through Ion Mobility
- • [MISO] MINT-ST: Multi-Dataset Integration and Pretraining for Histology-Based Spatial Transcriptomics Gene Expression Prediction
- • [MISO] Distributed Genetic Effects on Human Brain Structure Emerge Across Multiple Spatial Scales
- • [ML-CDS2026] Enabling Vision and Cross-Modal Learning for Multimodal Stroke Recurrence Prediction: An Interpretable Two-Step Framework
- • [ML-CDS2026] Quantifying Contributions within Multimodal Fusion for Clinical Decisions
- • [ML-CDS2026] MediRely: Reliability-Aware Retrieval for Robust Multimodal Clinical Decision Support
- • [ML-CDS2026] Multimodal and Longitudinal Modeling for Predicting Alzheimer’s Disease Progression
- • [MLCN-2026] Probability-Invariant Random Walk Learning on Gyral Folding-Based Cortical Similarity Networks for Alzheimer’s and Lewy Body Dementia Diagnosis
- • [MLCN-2026] Paramagnetic Rim Lesion Instance Segmentation in Multiple Sclerosis Using Conditional Convolutions
- • [MLCN-2026] SARAR: Shortcut-Aware 3D Brain MRI Question Answering via Retrieval-Augmented Reranking
- • [MLCN-2026] Implicit Neural Representations for Modeling the Accumulation of Tau Protein in the Brain
- • [MLCN-2026] Selection of Informative Variables in Y-Aware Framework: Insights from Genetic and Behavioural Data
- • [MLCN-2026] Heterogeneous Reservoir Dynamics Reveal Disease-Specific Temporal Fingerprints
- • [MLCN-2026] MEROS: Multi-view Expert Routing in Ordinal Space for MDD Spectrum Assessment
- • [MLCN-2026] Toward Personalized Dyslexia Classification via Dynamic Functional Connectivity and Explainable AI
- • [MLCN-2026] From Blood to Brain: Uncertainty-Aware Adaptive Fusion for Alzheimer’s Staging and Progression Under Incomplete Multimodal Profiles
- • [MLCN-2026] TIIC: Tabular Integration of Imaging and Clinical Data for Interpretable Multimodal Inference for Alzheimer’s Disease
- • [MLCN-2026] A Unified Brain MRI Reporting Framework Built on CoT-Guided VLM and Expert Models
- • [MLCN-2026] Few-Shot Cross-Site Domain Generalization for Multi-Site Autism Brain Network Classification
- • [MLCN-2026] Cross-Modality Structural Guidance in 3D Latent Diffusion for Robust FLAIR Super-Resolution
- • [MLCN-2026] Text-Guided Multimodal Multitask Learning for Brain Tumor Segmentation
- • [MLCN-2026] Network Alterations Precede Atrophy in Alzheimer’s Disease Progression Subtypes
- • [MLCN-2026] Do CNNs Learn Clinically Meaningful Imaging Representations? A Portable Multi-level Representation Audit for Brain Tumor MRI Classification
- • [MLCN-2026] Rapid Whole-Brain Parcellation
- • [MLCN-2026] Representation Learning for 3D Brain Imaging: A Benchmark
- • [MLCN-2026] EEG-LoGNet: Bridging Local Features and Global Contexts for EEG-Based Motor Imagery Classification
- • [MLCN-2026] MRI-Based Brain Age Estimation with Supervised Contrastive Learning of Continuous Representation
- • [MLCN-2026] SFINX: Structure-informed Functional-MRI Integration via xLSTM for Autism Diagnosis
- • [MLCN-2026] What Do Persistent Misclassifications Tell Us About Alzheimer’s Disease Detection using Structural MRI?
- • [MLCN-2026] Automated Segmentation and Height Measurement of Pituitary Gland
- • [MLCN-2026] Spatial Feature-wise Linear Modulation (SpFiLM) for Contrast Agent-Aware Brain Parcellation
- • [MLCN-2026] The Diagnosis a Reporter Leaves Unspoken: Surfacing Frozen Tumor Features for Brain-Tumor MRI Reporting
- • [MLCN-2026] Graph-Theoretical Task-Based Frontal Brain Network of Visual Working-Memory Load: An fNIRS Study
- • [MLMI] Learning Cross-Atlas Consistent Brain Disorder Representations via Disentangled Multi-Atlas Functional Connectivity Learning
- • [MLMI] CardioMamba: Multi-Frame Temporally Coherent Cine MRI Super-Resolution via State-Space Modeling
- • [MLMI] Clinical Tabular Data Enhances Multi-modal EEG-fMRI Classification of Alzheimer’s Disease
- • [MLMI] M-SFDA: Meta Network with Spatial Interaction for Source-Free Domain Adaptation in Prostate MRI Segmentation using Segment Anything Model
- • [MLMI] Hierarchical MoE for Multi-Modal ILD Diagnosis
- • [MLMI] Representation Matters: Rethinking Domain Generalization in Polyp Segmentation
- • [MLMI] SG-VIB: Salience-Gated Variational Information Bottleneck for Robust Invariant Brain Graph Learning
- • [MLMI] SC-TauPath: How Structural Connectivity Differences Shape Tau Distribution in Alzheimer’s Disease
- • [MLMI] DeJEPA: Non-Contrastive Self-Supervised Learning for Voxel-Level Representations
- • [MLMI] Anatomy-Constrained Neural Dynamics Learning with Function-Structure Coupling for Cognitive Decline Analysis
- • [MLMI] Spatially Invariant Multi-Task Learning for Liver Ultrasound–MRI Registration
- • [MLMI] A Unified 3D Vision-Language Framework for Structured Multi-Study Volumetric Report Generation
- • [MLMI] Efficient Test-Time Optimization via Knowledge Distillation for Modality-Agnostic Medical Image Registration
- • [MLMI] Optimizing 3D Diffusion Models for Medical Imaging via Multi-Scale Reward Learning
- • [MLMI] Decoding Phenotypes: A Framework for Fusing Genomic Language Models and Neuroimaging
- • [MLMI] Energy-Mamba: A Physics-Constrained State-Space Model for Medical Image Classification
- • [MLMI] Distributional Mutual Correction for Semi-Supervised Pancreas Segmentation
- • [MLMI] CIV-DG: Conditional Instrumental Variables for Domain Generalization in Medical Imaging
- • [MLMI] Guarantees That Survive a Missing Scan: Modality-Conditional Conformal Prediction for Multimodal Medical Diagnosis
- • [MLMI] Reducing False Positives in Pancreatic Tumor Segmentation via Multi-Scale Texture Enhancement and Curriculum Learning
- • [MLMI] Beyond Single View: Anatomy-Aware Rib Fracture Diagnosis with Multi-View Aggregation
- • [MLMI] GAIZ: Automated Detection of Geographic Atrophy Biomarkers via Volumetric OCT using Novel Morphological Objectives
- • [MLMI] Flow Matching Meets 3D Curvilinear Structure Segmentation in Medical Imaging
- • [MLMI] Rethinking Medical Landmark Localization with Prototype Learning-based Progressive Offset Correction
- • [MLMI] Clinical Hierarchy and Regional Awareness for Multi-Label Classification of Magnetocardiograms
- • [MLMI] Organ-Aware Longitudinal Report Generation for Abdominal Tumor Assessment from 3D Contrast-Enhanced CT
- • [MLMI] Generalist-Specialist Mixture-of-Experts for Rare Pathology Detection in Multimodal Imaging
- • [MLMI] Leakage-Controlled Resting-State Connectome Classification of Schizophrenia: A Nested Cross-Validation Audit of the COBRE Cohort
- • [MLMI] A Task-Controllable Semantic Diffusion Model for Whole-Body PET Enhancement
- • [MLMI] What Matters is the Prompt: Prompt Sensitivity and Prompt Generation in Foundation Models for Lung Nodule Segmentation
- • [MLMI] Augmentation Strategy for DINO in Glaucoma Classification
- • [MLMI] Learn the Metric, Not the Deformation: A Small Contrastive Encoder for Cross-Modal Histology-MRI Registration
- • [MLMI] Improving Medical Image Generative Models with Fréchet Distance Loss
- • [MLMI] SCALE: Structure-preserving Cycle-consistent Atlas Learning for 4D Infant Cerebellum Atlas Construction
- • [MLMI] SAGE-MoE: Subject-Adaptive Genetic-Environmental Guided Mixture-of-Experts for Early Diagnosis of Alzheimer’s Disease
- • [MLMI] Deep Unrolled Networks in Representation Space Applied to MRI Reconstruction
- • [MLMI] PPCNet: Projection-Conditioned Point Cloud Reconstruction of Spinal Vertebrae from Biplanar Radiographs
- • [MLMI] CEVAR: Centerline Embedding Extraction for Endovascular Aneurysm Repair
- • [MLMI] Long-Term Prediction of Atrial Fibrillation Severity from Echocardiography Video
- • [MLMI] CirrGuide: A Deep Cascaded Framework for Liver Cirrhosis Segmentation and Severity Classification from T2-Weighted MRI
- • [MLMI] Benchmarking Self-Supervised Pretraining Strategies for Chest X-Ray Triage and Out-of-Distribution Transfer
- • [MLMI] HyProDINO: A Hybrid Prototype Guided DINO Framework for Cross-Domain Few-Shot Medical Image Segmentation
- • [MLMI] Towards Distortion–Perception-Balanced MRI Reconstruction using Posterior-Mean Rectified Flow
- • [MLMI] LEAP-AD: An LLM-Encoded Brain-Heart Axis Prior Injection Framework for Brain-Only Early Alzheimer’s Disease Diagnosis
- • [MLMI] Inter-Slice Acquisition Budget Allocation for Pathology Aware Accelerated MRI
- • [MLMI] Knowledge-injection for small-cohort medical image learning
- • [MLMI] Diffusion-based Zero-shot Image Quality Transfer for Low-Field MRI Enhancement with Nonlinear Conjugate Gradient
- • [MLMI] Beyond Discrimination: Recalibrating Echocardiographic Scar Prediction
- • [MLMI] LEEWAY: Same Anatomy, Same Score, Different Verdict Using Paired Falsification Tests in Dental CBCT
- • [MLMI] Beyond Global Macro-AUC: Class-Wise Modality Contribution in Multicentre MRI-Based Glioma Grading
- • [MLMI] Prevalence calibration as shortcut mitigation
- • [MLMI] MaLViL: Multi-axis Low-rank Vision-LSTM for Medical Image Segmentation
- • [MLMI] Data leakage and external validation in lung CT segmentation
- • [MLMI] Train Multimodal, Deploy Unimodal: Hierarchical Cross-Modality Distillation for Brain Disease Diagnosis
-
• [MLMI] Gaussian Meta-Space Augmentation for Stacking Ensembles in Multimodal IPMN Risk Stratification
- Nelson, Max A.; Tasci, Eminenur Sen; Wang, Zhixiang; Zhou, Zongwei; Aktas, Halil Ertugrul; Bejar, Andrea M.; Keles, Elif; Hong, Ziliang; Taflan, Sıtkı Safa; Tasci, Muhammed Enes; Miller, Frank H.; Wallace, Michael B.; Keswani, Rajesh N.; Durak, Gorkem; Bagci, Ulas;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MLMI] Inference-Time Orthogonal Seeding Enables Geometry-Aligned 3D Organ Segmentation for Slice-Propagation Methods
- • [MLMI] Model-based distortion correction for Magnetic Resonance Echo Planar Imaging
- • [MLMI] Optimizing Design Choices for Endoscopic Ulcer Segmentation: Foundation Models, Decoders, and SAM-based propagation
- • [MLMI] A coarse to fine approach to magnetic resonance spectroscopy quantification
- • [MLMI] HyperAMS-Net: Adaptive Multi-Scale Spatial Hypergraph Network for Brain Disorder Classification
- • [MLMI] HyperPatch: Hypercolumns for Transformer Backbones in Medical Segmentation
- • [MLMI] Efficient and Faithful Retrieval-Augmented Medical VQA via Intention-Guided On-Policy Self-Distillation
- • [MLMI] Are robust loss functions still relevant for medical image segmentation with noisy labels?
- • [MLMI] SliceLift: Slice-to-Volume Feature Lifting for Volumetric Pancreatic Cyst MRI Segmentation
- • [MLMI] GazeRefine: Expert Gaze as a Test-Time Prompt for Training-Free Medical Image Segmentation
- • [MLMI] Two-Stage Structure-Conditioned Vessel Segmentation and Keypoint Localization for DIEP Flap Planning
- • [MRIxFields2026] Task-Adaptive 3D Cross-Field MRI Translation via Field-Conditioned Content-Style Pretraining
- • [MRIxFields2026] Unified Source-Conditioned Translation with Shared-Cycle Refinement for Any-to-Any Cross-Field Brain MRI
- • [MRIxFields2026] Field-Conditioned MRI Field-Strength Translation for the MRIxFields2026 Challenge
- • [MRIxFields2026] Fast Cross-Strength Multi-Contrast Brain MRI Translation using Latent Bridge Matching
- • [MRIxFields2026] Rethinking Unpaired Data in Unified Cross-Field MRI Synthesis
- • [MRIxFields2026] Modality-Adaptive Contrastive and Supervised Learning for Multi-Field MRI-to-7T Synthesis
- • [MRIxFields2026] Latent Conditional Rectified Flow for MRI Synthesis Across Modalities and Field Strengths in the MRIxFields2026 Challenge
- • [MRIxFields2026] A U-Net++ Framework with Self-Supervised Pretraining for Low-to-High Field MRI Translation
- • [MRIxFields2026] FieldMorphUNet: Conditional Multi-Field MRI Translation with Structure-Scale Decoupling
- • [MRIxFields2026] A Unified Conditioned Swin-UNETR CUT Model for Cross-Field Brain MRI Harmonisation
- • [MRIxFields2026] Conditional Flow Matching for Cross-Field MRI Harmonisation
- • [MRIxFields2026] DINOv3-PE-DPT: Frozen Public DINOv3 Weights for Cross-Field Brain MRI Translation
- • [MRIxFields2026] Multi-Field MRI Synthesis with Paired–Synthetic–Paired Latent Diffusion
- • [MRIxFields2026] FieldFiLM: A Unified Conditional Generator for the MRI Field-Strength Continuum
- • [MRIxFields2026] Unified Cross-Field Multi-Contrast MRI Translation and Harmonization
- • [MRIxFields2026] N5: A Unified FiLM-Conditioned Output-Stack Cascade for Cross-Field Brain MRI Translation
- • [MRIxFields2026] Physics-Conditioned Latent Diffusion Bridges for Ultra-Low-Field to Multi-Field MRI Synthesis
- • [MRIxFields2026] Any-to-Any Brain MRI Field Translation using a Unified Multi-Modality, Multi-Field Conditional Diffusion Model
- • [MRIxFields2026] Cross-Field MRI Synthesis with an Unpaired Neural Schrödinger Bridge
- • [MRIxFields2026] Pairing-Independent Cross-Field MRI Translation: Synthetic Supervision and Structure-Preserving Domain Adaptation for Ultra-Low-Field to High-Field Synthesis
- • [MRIxFields2026] Anatomy-Anchored Empirical Domain Randomization for Cross-Field T1-Weighted MRI Translation
- • [MRIxFields2026] FieldRF: Anatomy-Conditioned 3D Rectified Flow for Unified Cross-Field MRI Harmonization
- • [MVAA] Boundary-Aware and Semi-Supervised Baselines for Multi-Modal Mitral Valve Anatomy Analysis
- • [MVAA] Robust Multimodal Mitral Valve Segmentation with Volumetric Anchors and Uncertainty-Guided Surgical-Frame Refinement
- • [MVAA] Task-Specific Segmentation Pipelines for the MVAA Challenge
- • [MVAA] From CT to Surgical Video: Robust Mitral Valve Segmentation across Multimodal Clinical Imaging
- • [MVAA] Failure-Mode-Driven Multimodal Mitral Valve Segmentation for the MVAA 2026 Challenge
- • [MVAA] Label-Limited Mitral Valve Segmentation Across CT, TEE, and Surgical Video: MVAA 2026
- • [MVAA] Mitral Valve Segmentation in CT, 3D TEE, and Surgical Video
- • [MVAA] MVAA-Seg: A Multi-Stage Segmentation Framework for Mitral Valve Anatomy Analysis
- • [MVAA] Baseline Method of the MVAA 2026 Challenge for Multimodal Mitral Valve Segmentation
- • [MVAA] Solution for MVAA challenge 2026: Ensemble, Tool-paste Augmentation and Tool-free View Generation
- • [MVAA] ValveMix: A Unified Semi-Supervised Framework for Multimodal Mitral Valve Anatomy Segmentation
- • [MVAA] Multimodal Mitral Valve Segmentation: Mesh-Based 3D and Depth-Transfer Learning
- • [MVAA] Task-Specific Multimodal Mitral Valve Segmentation for MVAA 2026
- • [MVAA] A Modality-Specific Ensemble for Multimodal Mitral Valve Anatomy Analysis
- • [MVAA] Modality-Tailored Mitral Valve Segmentation: Custom Architectures and Robust Noise Suppression
- • [MVAA] Modality-Aware Segmentation of Mitral Valve Anatomy in CT, 3D TEE, and Surgical Video
- • [MVAA] BEAT: Boundary-aware Efficient Anatomy-Transfer for Multimodal Mitral Valve Segmentation
- • [MVAA] SurgNeXt: Structured Semantics and Target Presence for Mitral Valve Segmentation in Surgical Video
- • [MVAA] MVAA-UniSeg: A Query-Conditioned Universal Model with Modality-Specific Experts for Mitral Valve Segmentation
- • [MVAA] BM-SAM3D: Boundary-Aware Adapter and Mamba Fusion Enhanced SAM for 3D Ultrasound Mitral Valve Segmentation
- • [MVAA] Task-Specific Segmentation Frameworks for Multi-Modal Mitral Valve Tasks in MVAA2026
- • [MVAA] Comprehensive Multi-Modal Mitral Valve Segmentation across Cardiac CT and Echocardiography
- • [MVAA] Mitral Valve Multi-modality Adaptive Segmentation
- • [MVAA] ReGate-MV: Role-Aware Region–Surface Expert Composition with Structural Repair for Mitral Valve Segmentation
- • [MVAA] Hybrid-Supervised Multi-Task Network for Multi-Modal Perioperative Mitral Segmentation
- • [MVAA] Modality-Specific Mitral Valve Segmentation Across CT, 3D TEE, and Surgical Video
- • [MVAA] Multi-Modal Mitral Valve Anatomy Analysis: Supervised and Semi-Supervised Segmentation Across CT, Ultrasound, and Surgical Video
- • [MVAA] Semi-Supervised nnU-Net with Weak–Strong Consistency and Boundary Refinement for Mitral Valve Segmentation
- • [MVAA] Mitral Valve Anatomy Segmentation for Multimodal Data
- • [MVAA] RATS-SAM: Reasoning with Surgical Evidence for Mitral Valve Segmentation
- • [MVAA] Mitral-Valve Segmentation Across CT, TEE, and Surgical Video
- • [MVAA] Geometry-Aware and Semi-Supervised Ensembles for Multimodal Mitral Valve Segmentation
- • [MVAA] When Does Unlabelled Data Help? A Shift-Aware Semi-supervised Study of Multimodal Mitral Valve Segmentation
- • [MVAA] Formulation Diversity and Boundary-Aware Postprocessing for Mitral Valve Segmentation in 3D TEE and 2D Surgical Video
- • [MVAA] Multimodal Mitral Valve Segmentation with Cross-Validation Ensembles and Pseudo-label Retraining
- • [MVAA] StateMV: Trust-Gated Anatomy-State Transitions for Multimodal Mitral Valve Segmentation
- • [MVAA] A Multimodal Segmentation Pipeline for Mitral Valve Anatomy Analysis in Cardiac CT, 3D Transesophageal Echocardiography, and Surgical Video
- • [MWM] Inside the Preparation: Multimodal CBCT–Intraoral Scan Fusion for Dental Preparations
- • [MWM] Towards Reliable CXR Diagnosis through Disentangled Multi-View Learning Enhanced with Structured Concepts
- • [MWM] Pathology-based Ordinal Multiple Instance Learning Framework for Esophageal Cancer Tumor Regression Grading
- • [MWM] Future Querying: Can LLMs Serve as Implicit Medical World Models?
- • [MWM] SurgGenesis: A Generative Surgical World Model for Future-Aware Surgical Understanding
- • [MWM] Multimodal Data Integration via Digital Twins: Analysis of Aneurysm Rupture Risk Factors
- • [MWM] Intervention-Aware Clinical World Model for Post–Op Outcome Forecasting in Cardiology
- • [MWM] Multi-surface Spatiotemporal Anatomy Transfer for Virtual Reality-based Obstetrics Simulation
- • [MWM] An Organoid World Model: Forecasting Self-Supervised Feature Dynamics for Early Chemosensitivity Prediction
- • [MWM] Did the Grid Erase the Event? EndoClock for Auditing Medical World-Model Pipelines
- • [MWM] Representation-Aware Multimodal Integration for Small-Sample pCR Prediction in Rectal Cancer
-
• [MWM] Synthesizing Longitudinal Cutaneous Neurofibroma Imaging for Digital-Twin Burden Quantification
- Sadée, Christoph; Dils, Alex; Sangani, Krish; Rubino, Lillian; Ferenchick, Alexander; Wadhwa, Varun; Poddar, Anushka; Onyemeh, Tobenna; Onah, Zimuzo; Sharma, Dhruv; Bae, Jackson; Van Puyvelde, Max; Romo, Carlos; Jen, Melinda; Onodugo, Nkiru; Akinkugbe, Ayesha; Xu, Qinmei; Kong, Qingtao; Yang, Rui; Sokunbi, Aisha; Yao, Shaoxiong; Huang, Haomiao; Okoye, Ifeoma; Gevaert, Olivier; Sarin, Kavita;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MWM] Adversarial-Contrastive Domain Generalization for Cross-Site Autism Spectrum Disorder Classification from Resting-State fMRI
- • [MWM] TNCMeasure: Anatomy-Guided and Geometry-Constrained Vision-Language Learning for Thyroid Nodule-to-Capsule Distance Measurement
- • [MWM] Stochastic High-Frequency Modeling for Uncertainty-Aware Synthetic CT Generation in Radiotherapy
- • [MWM] MedWorld-Lite: A Missingness-Aware Personalized Framework for ICU Medical World Modeling
- • [MWM] ICUWorld-QR: A Residual Latent World Model for Hourly ICU Physiology
- • [MWM] Sequence-Specific LoRA Adaptation of a Vision Foundation Model for Patient-Level csPCa Classification from Biparametric MRI
- • [MWM] A Federated Probabilistic Digital Twin for Adverse-Event Risk in Aesthetic Medicine
- • [MWM] CalTwin: Calibrated Shift-Robust Medical World Models via Fisher-Information Regularization
- • [MedAGI] A Resource-Constrained Evaluation of Lightweight Adaptation for Cross-Dataset Chest X-ray Report Generation
- • [MedAGI] CMRVision: A Foundation Model for Cardiac MR Image Analysis
- • [MedAGI] U-VLM: Hierarchical Vision Language Modeling for Report Generation
- • [MedAGI] Frequency Adapter with SAM for Generalized Medical Image Segmentation
- • [MedAGI] A Benchmark of (MRI-) Foundation Models to Predict IDH Mutational Status in Glioma
- • [MedAGI] Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos
- • [MedAGI] Semi-Supervised Few-Shot Adaptation of Vision-Language Models
-
• [MedAGI] Specializing Foundation Models via Mixture of Low-Rank Experts for Comprehensive Head CT Analysis
- Yoo, Youngjin; Liu, Han; Georgescu, Bogdan; Zhang, Yanbo; Grbic, Sasa; Baumgartner, Michael; Re, Thomas J.; Das, Jyotipriya; Ullaskrishnan, Poikavila; Eibenberger, Eva; Chekkoury, Andrei; Bodanapally, Uttam K.; Nicolaou, Savvas; Sanelli, Pina C.; Schroeppel, Thomas J.; Lui, Yvonne W.; Gibson, Eli;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MedAGI] TubeMLLM: A Foundation Model for Topology Knowledge Exploration in Vessel-like Anatomy
- • [MedAGI] B-MIM: Biased Masked Image Modeling for Generalizable Segmentation of Fine-Grained Anatomical Structures
- • [MedAGI] MedDocBench: A Benchmark for Medical Document Visual Question Answering
- • [MedAGI] TopoMedKD: Shape- and Topology-Aware Distillation of Zero-Shot MedSAM for Compact Medical Image Segmentation
- • [MedAGI] A Comparative Evaluation of Structural MRI Foundation Models for Age, Sex, and Body-Mass Index Predictions
- • [MedAGI] Coherence Is Not a Green Light: The Limits of Self-Consistency as a Label-Free Reliability Proxy for Medical Vision–Language Models
- • [MedAgent] CLAP-4-QnA: An Agentic Graph-RAG Pipeline for SNOMED-CT-Grounded Clinical Question Answering
- • [MedAgent] Vision-Language Model Guided Semantic Curation for Large-Scale Medical Data Cohorts
- • [MedAgent] From Metrics to Insight: Agent-Based Comprehensive Evaluation of Medical Image Segmentation
- • [MedAgent] Which Tool Response Should I Trust? Towards Tool-Expertise-Aware Chest X-ray Agent with Multimodal Agentic Reinforcement Learning
- • [MedAgent] A Multi-Agent Framework for Automated MRI Reporting in Glioma: A Real-World Clinical Validation
- • [MedAgent] A Fully Local Agentic LLM Architecture for Tool Invocation in Medical Imaging
- • [MedAgent] Why Benchmark Accuracy Fails to Measure Clinical Reasoning in Medical Vision-Language Models: Toward Clinical Adversarial Validation
- • [MedAgent] Retrieval-Augmented Longitudinal Reasoning for OCT Change Detection and Forecasting: A Trajectory-Aware Multimodal RAG Framework with Calibrated Vision-Language Models
- • [MedAgent] FRAC-MAS: A Safe and Explainable Multi-Agent System for Fracture Diagnosis
- • [MedAgent] EndoRAG: An Agentic Retrieval-Augmented Generation Framework for Endocrinology Question Answering
- • [MedAgent] Attack Your Own Findings: A Falsification Agent Framework for Biomedical Discovery, Benchmarked on Four Errors We Actually Made
- • [MedAgent] Ask4VG: A Risk-Aware Question Selection Agent for Reducing Prior-Driven Answers in Medical VQA
- • [MedAgent] Disentangling Perception and Reasoning in Zero-Shot Multimodal LLMs for Ultrasound Diagnosis
- • [MedAgent] Towards Automated Cardiac MRI Assessment: A MultiAgent CAD Framework for Functional Analysis and Tissue Characterization
- • [MedAgent] Wasserstein Equilibrium Decoding for Reliable Medical Visual Question Answering
- • [MedAgent] Echo-CoPilot: A Multiple-Perspective Agentic Framework for Reliable Echocardiography Interpretation
- • [MedAgent] Can Coding Agents Build Robust Baselines? A Skill-Based Approach for Automating the Medical Imaging Model-Development Pipeline
- • [MedAgent] A Label-Efficient On-Device QC Agent for MRI Segmentation under Domain Shift
- • [MedAgent] LongCXR-Agent: Query-Driven Tool Selection for Longitudinal Chest X-ray Reasoning
- • [MedAgent] MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring
- • [MedAgent] AgentQC: Policy-Constrained Agentic Assessment of Task-Aware Reliability in Medical Imaging Datasets
- • [MedAgent] A Modular Agent for Reliable and Auditable Spatial Relation Verification in CT Scans
- • [MedAgent] HPOQuest: A Rare-Disease Diagnostic Agent Using Active Phenotype Acquisition
- • [MedAgent] CaseWeaver: A Multi-Agent Framework for Multimodal Virtual Clinical Case Generation
- • [MedAgent] When to Request and Whether to Trust: A Two-Decision Imaging Agent for Pleural Effusion Assessment
- • [MedAgent] Evaluating Procedural Tool-Calling in AI Agents for Lung Cancer Workflows
- • [MedAgent] HarmoAgent: An Autonomous LLM Agentic Framework for Adaptive and Traceable Multi-Site MRI Harmonization
- • [MedAgent] Agentic Visual Evidence Construction and Review Architecture for Medical VQA
- • [MedAgent] LongAgent: History-Guided Agentic Search for Longitudinal Outcome Prediction
- • [MedAgent] MorphoOrgaAgent: A Foundation-Model-Based Multi-Agent System for Autonomous Organoid Analysis
-
• [MedAgent] Agents Catching Agents: Shortcut Cascades and Benchmark Gaming in Clinical Multi-Agent Systems
- Ordóñez, Sebastián Andrés Cajas; Moran, Yehudhah Kennedy Rodríguez; Munnangi, Agastya; Marzullo, Aldo; Osorio, Felipe Ocampo; Bui, Quang; Shahin, Mohammad; Grewal, Armaan; Kwesiga, Emmanuel Paul; Li, Anqi Peter; Nanyonjo, Josephine; Panchal, Aaditya; Bhutani, Arshnoor; Jaiswal, Nikhil; Patel, Milit S.; Lange, Maximin; Umeton, Renato; Celi, Leo Anthony;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [MedAgent] AgentFL-Bench: Benchmarking Small Language Models for Fairness Governance in Federated Clinical AI
- • [MedAgent] MechAgent: Active Mechanism Falsification for Agentic Cross-Species Medical Reasoning
- • [MedAgent] Too Tight or Too Loose: How VLM Persona Committees Miscalibrate Inter-Rater Ambiguity in Medical Image Segmentation
- • [MedAgent] Toward Anxiety-Reducing Conversational AI Agents for Breast Cancer Care
- • [MedAgent] FaceLandmarkAgent: A Training-Free Planner-Critic Agent for 3D Facial Landmarking via Spatial-Semantic Reasoning
- • [MedAgent] GLIO-FAILSAFE: Failed Experiment or Negative Result?
- • [MedAgent] Absent-Byte Diagnoses: Auditing Structured Medical VLM Interfaces
- • [MedReason] Answer Readout as a Major Confounder in Medical Multiple-Choice Visual Question Answering
- • [MedReason] CLINIC-VQA: Reasoning-Aware MLLM with Explicit Clinical Reasoning Traces for Medical Visual Question Answering
- • [MedReason] MIRA: Modality-Adaptive Image-Grounded Reasoning and Answering for Medical Visual Question Answering under Domain Shift
- • [MedReason] Option-Aware Retrieval and Task-Specific VLM Adaptation for Medical VQA
- • [MedReason] A Task-Routed Hybrid Vision–Language System for Medical Visual Question Answering, and a Calibrated Analysis of the Open-Ended Reasoning Ceiling
- • [MedReason] The Label Is Not the Answer: Output-Schema Anchoring in Medical Multimodal MCQ Evaluation
- • [MedReason] Two-Stage LoRA Adaptation of Qwen3-VL for Image-Grounded Medical Visual Question Answering
- • [MedReason] GrADe: Grouped Adapter Decoding for Medical Visual Question-Answering under Domain Shift
- • [MedReason] Medical Visual Question Answering with Length-Prior Arbitration and Reward-Aligned GRPO
- • [MedReason] Cross-Model Candidate Selection for Grounded Medical Visual Reasoning: A Systematic Comparison of Fourteen Fine-Tuned Vision-Language Models
- • [MedReason] A Parameter-Efficient Vision–Language System for Reasoning-Grounded Medical Visual Question Answering under Domain Shift
- • [MedReason] Task-Routed Low-Rank Adaptation with Grounded Supervision for Medical Visual Question Answering
- • [MedReason] Candidate-Expanding Routing with Permutation-Stabilized Experts for Mixed-Format Medical VQA
- • [MultiTab] Uncertainty-Aware Multimodal Fusion for Oral Lesion Classification
- • [MultiTab] Whole-Body MRI Classification via Prompt-Based Clinical Conditioning
- • [MultiTab] Predicting Postprandial Glycemic Response from Meal Images, Clinical Variables, and Gut Microbiome Information
- • [MultiTab] Mr.Dec: Daily-Scale Longitudinal Multimodal Modeling for 30-Day Readmission Prediction
- • [MultiTab] MIMIC-CXR-DB: An Admission-Linked, Ontology-Grounded Multimodal Resource Built on MIMIC-CXR and MIMIC-IV
- • [MultiTab] MMAP: Multimodal Missing-Aware Pretraining for Longitudinal Alzheimer’s Prediction
- • [MultiTab] Tabular Encoder Generalization Under Clinical Constraints for Multi-Modal Risk Prediction
- • [MultiTab] JPathGene: Cross-Modal Latent Diffusion Predictive Learning between Histopathology Images and Genetic Profiles
- • [MultiTab] Predicting Knee Osteoarthritis Pain Trajectories from Multimodal Longitudinal Data
- • [MultiTab] A Reproducible Public Benchmark for End-to-End Machine Learning from Multimodal Tabular Data in Cancer Recurrence Prediction
- • [MultiTab] Conditional Intervention Analysis: Toward Identifying Causal Features in Tabular Multimodal Data
- • [MultiTab] Single-Pass Conformal Cross-Modal Anomaly Screening with Tabular Foundation Models
- • [ODIN] Teeth2Point: A Two-Stage Dental CBCT ROI-to-Point Segmentation Framework
- • [ODIN] Registration of 2D intraoral radiographs to 3D CBCT using modality-specific encoding
- • [ODIN] Comparing Pretraining Strategies for Intra-Oral Image Analysis Under Limited Annotation Budgets
- • [ODIN] AI-Based Landmark Detection for Condylar Asymmetry Assessment in Patients with Juvenile Idiopathic Arthritis
- • [ODIN] Attention Voting for 3D Cephalometric Landmark Detection
- • [ODIN] PAINT: Projection-Aware Implicit Neural Transformer for Soft-Tissue Surface Generation in Orthognathic Surgical Planning
- • [ODIN] Automatic Cephalometric Landmark Localization on CBCT-Derived Digitally Reconstructed Radiographs for Skeletal Malocclusion Classification
- • [ODIN] Diagnosis-Aware Multimodal Retrieval for Paired CBCT Scans and Clinical Notes
- • [ODIN] From TMJ Localization to Detection of Osteoarthritic Features: An Anatomically Guided 3D Deep Learning Pipeline for Cone-Beam CT
- • [ODIN] CI-MAS: Clinically Informed Restoration-Configuration Simulation for Dental CBCT Metal Artifact Reduction
- • [ODIN] A Public Dataset for Tooth Segmentation in Multi-View Intraoral Photographs
- • [ODIN] Fluency Is Not Faithfulness: Diagnosing and Repairing Confabulation in LLM Report Generation on ToothFairy4 CBCT
- • [ODIN] Anatomy-Constrained Duplication Loss for Tooth Detection in Panoramic Radiographs
- • [ODIN] Automated Dental Arch Curve Detection from CBCT: A Geometric and Learning-Based Platform
- • [ODIN-challenges] Registration Teaches Registration: Transform-Derived Crown Guidance for Semi-Supervised CBCT–IOS Alignment
- • [ODIN-challenges] Geometry-Guided Identity Correction for Semi-Supervised CBCT Tooth and Root-Canal Segmentation
- • [ODIN-challenges] Handedness-Aware Cross-Attention SVD for Multimodal Dental Registration
- • [ODIN-challenges] Landmark-Guided Coarse-to-Fine Registration of Intraoral Scans and Cone-Beam CT
- • [ODIN-challenges] DentSAFER: Action-Aware Field Retrieval for Structured Dental CBCT Reporting
- • [ODIN-challenges] Clinically Guided Rendering for Orthodontic Report Generation
- • [ODIN-challenges] Seeing the Bite: Learned Cross-Arch Occlusion Grounding for Orthodontic Report Generation from Intraoral Scans and Photographs
- • [ODIN-challenges] GQ-TSR: Guarded Query Teacher–Student Retrieval for CBCT-to-Clinical Record Prediction
- • [ODIN-challenges] Resource-Aware Retrieval Baselines for CBCT-to-Report Generation in ToothFairy4
- • [ODIN-challenges] Semi-Supervised Dental CBCT Report Generation via Entity-Aware Dual-Space Retrieval
- • [ODIN-challenges] CBCT Tooth and Pulp Segmentation via Watershed Fusion and Lightweight Dual-Branch nnU-Net
- • [ODIN-challenges] Entity-Constrained CBCT Retrieval for Low-Resource Dental Record Completion
- • [ODIN-challenges] CPMT: Cross-Plane Masked Prototype-Gated Mean Teacher for CBCT-to-Clinical Record Prediction
- • [ODIN-challenges] Medication-Safe Dual-Encoder Retrieval for Structured Dental Report Prediction from CBCT
- • [ODIN-challenges] Coordinate-Aware Point Cloud Registration for Crown-to-Root Alignment in CBCT and Intraoral Scans
- • [ODIN-challenges] Segmentation-Guided 3D Dental ROI Transformer for Structured Clinical Report Generation from CBCT
- • [ODIN-challenges] Global-to-Local Tooth and Pulp Instance Segmentation in Dental CBCT
- • [ODIN-challenges] RGBite: Vision-Language Report Generation for the ODIN 2026 Challenge
- • [ODIN-challenges] From Voxels to Views to Reports: A Segmentation-Guided VLM Pipeline for CBCT Report Generation
- • [ODIN-challenges] OrthoScribe: Training-Free Multimodal Orthodontic Report Generation via Photographic Retrieval and 3D Geometry Correction
- • [ODIN-challenges] MMLVM: Geometry-Aware Multimodal Language Modeling for Orthodontic Report Generation
- • [OMIA] Towards a Robust and Explainable Pipeline for Diabetic Retinopathy Classification through Quality-Aware GenAI Image Restoration
- • [OMIA] Cross-Client Gradient Alignment for Federated Multi-Source Fundus Diagnosis
- • [OMIA] OphthaAgent: Learning Cognitive Prudence for Reliable Fundus Diagnosis via Tool-Augmented Reinforcement Learning
- • [OMIA] Structure-Function Linking with Gated Sparse Cross-Attention for Visual Impairment Categorization Using Fundus Imaging and Visual Electrophysiology
- • [OMIA] Retina-RAG: Retrieval-Augmented Vision–Language Modeling for Joint Retinal Diagnosis and Clinical Report Generation
- • [OMIA] A Phased Self-Teaching Framework for Hyperreflective Foci Segmentation in OCT
- • [OMIA] When to Denoise Longitudinal Visual Field Labels: Anchor-Preserving Supervision under Short Follow-up
- • [OMIA] Beyond the Last Frame: Temporal Modelling of Fluorescein Angiography for Hyperfluorescence Classification
- • [OMIA] ReGraFT: Broad Multi Label Retinal Disease Classification on MuRFiD
- • [OMIA] Fundus Image Quality Assessment Based on Frequency-Domain Degradation Transfer and Generative Adversarial Networks
- • [OMIA] Counting Is Not Enough: Spatially Explicit Formulations for AOSLO Cone Photoreceptor Quantification
- • [OMIA] ArTiSan: Archetype-Aware TimeSformer for Fast Glaucoma Progression
- • [OMIA] Beyond Dice: Clinically Meaningful Large-Scale Retinal Artery/Vein Segmentation
- • [OMIA] Benchmarking Vision-Language Models for Image-Based Infectious Versus Non-Infectious Uveitis Classification
- • [OMIA] Medical Prior-Guided Few-Shot Adaptation of BiomedCLIP for Infectious and Non-Infectious Uveitis Classification
- • [OMIA] Topology-Aware Staged Diffusion for Multi-Vendor Retinal OCT Fluid Segmentation
- • [OMIA] Compress to Scale: Semantic Token Reduction for High-Resolution Retinal Image Analysis
- • [OMIA] A Novel Recursive Mamba Encoding for Retinal Artery-Vein Segmentation in MedTech Applications
- • [OMIA] Diagnosing Adaptation Failure Modes in Foundation Models for RNFL Thickness Prediction
- • [OMIA] In Defense of OCTA: The Reconstruction-Utility Gap in OCT-to-OCTA Synthesis
- • [OMIA] A Multitask Learning Framework for Predicting Diabetic Retinopathy Progression via State Transition Matrices
- • [OMIA] Local scale-free fluctuation analysis for angle closure Detection in AS-OCT images
- • [OMIA] Weakly Supervised Retinal Layer Segmentation in OCT
- • [Off-Grid] 4D Triangle Splatting Reconstruction of Dynamic Endoscopic Scenes from Monocular Videos
- • [Off-Grid] Neural CDEs for Variable-Length qMRI: IVIM and R2* Estimation in the Pancreas
- • [Off-Grid] Causal Spatio-Temporal Neural Distance Fields for Counterfactual Cardiac Anatomy
- • [Off-Grid] Learning Cardiac Motion Priors for Implicit Neural Representations
- • [Off-Grid] Overlap-Free Multi-Organ Shape Synthesis with Implicit Neural Representations
- • [Off-Grid] From Histology to in vivo MRI: An Implicit Neural Representation Framework for Medial Temporal Lobe Subregion Segmentation
- • [Off-Grid] INR-based FPCA for Efficient Analysis of Longitudinal Neuroimaging Data
- • [Off-Grid] Shape-guided Gaussian Splatting for Sparse-View X-ray 3D Reconstruction
- • [Off-Grid] Modelling Geographic Atrophy Progression using Implicit Neural Representations
- • [Off-Grid] Strain Rate Estimation from Ultrasound Channel Data
- • [Off-Grid] NIMOSEF-R: Neural Implicit Motion and Segmentation Functions with Riemannian Embedding Priors and Breath-Motion Correction
- • [Off-Grid] Hemodynamic Neural Field: Continuous Blood Flow Estimation in Vessel Geometries via Global Shape Conditioning
- • [Off-Grid] Primitive Representation Learning for Unsupervised Dynamic Contrast Enhanced MRI Reconstruction
- • [Off-Grid] Surface-Conditioned Implicit Reconstruction of Internal Anatomy for Automated Patient Positioning
- • [Off-Grid] The Right Prior for the Right Deformation: Rethinking Continuous Deformable Image Registration
- • [Off-Grid] Piecewise Positional Encodings (PPE) for Medical Image Representation
- • [Off-Grid] Implicit representations are dead. Long live explicit primitives!
- • [Off-Grid] Over-parameterising of optimisation for sparse 3D medical image registration
- • [Off-Grid] K-NeAS: Scalable Multi-Material CT Reconstruction Using Neural SDFs
- • [Off-Grid] Is Reconstruction Fidelity a Reliable Proxy for Segmentation in Medical INRs?
- • [Off-Grid] Neural Field Fourier Token Mixers for Medical Image Segmentation
- • [Off-Grid] Mirror and Map: Symmetric Latent Deformation Priors for Deformable Image Registration using Implicit Neural Representations
- • [Off-Grid] Probing implicit neural representations for biomedical image classification in weight space
- • [Off-Grid] Observation-Conditioned Latent Energy Priors for Sparse Implicit Neural Shape Completion
- • [PIPPI] SUPER-IVIM-DC-SUB: A Physics-Informed Subset Ensembling Framework for Robust Placental IVIM Analysis in Uncontrolled Maternal Diabetes
- • [PIPPI] Shape-DNA Spectral Analysis of Lesion Morphotypes in Paediatric-Onset Multiple Sclerosis
- • [PIPPI] Quality over quantity: data curation for automated angle of progression estimation in intrapartum ultrasound
- • [PIPPI] R2AoP: Reliable and Robust Angle of Progression Estimation from Intrapartum Ultrasound
- • [PIPPI] The effect of image resolution on texture and shape features derived from placental magnetic resonanceimages
- • [PIPPI] Aligning Fetal Anatomy with Kinematic Tree Log-Euclidean PolyRigid Transforms
-
• [PIPPI] Diffusion MRI Tract Analysis Separates Infants with Down syndrome from Typical Controls
- Styner, Martin; Garic, Dea; Nasir, Aleeshah; Azrak, Omar; Swanson, Meghan R.; Grzadzinski, Rebecca L.; Al-Ali, Khalid; Shen, Mark D.; Gerig, Guido; Girault, Jessica B.; Green, Ta’shawnna; St. John, Tanya; Pandey, Juhi; Zwaigenbaum, Lonnie; Estes, Annette M.; Wolff, Jason J.; Dager, Stephen R.; Schultz, Robert; Evans, Alan; Elison, Jed T.; Yacoub, Essa; Kim, Sun Hyung; McKinstry, Robert C.; Pruett Jr., John R.; Piven, Joseph; Botteron, Kelly N.; Hazlett, Heather C.; Marrus, Natasha;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [PIPPI] Longitudinal registration of human fetal brain MRI
- • [PIPPI] Mapping Structural Connectivity in the Neonatal Developing Brain using Multi-Component Tissue Modelling
- • [PIPPI] Multi-modal deep learning for fetal corpus callosum segmentation and characterization in MRI
- • [PIPPI] EMD-Regularized Heatmap Regression for 3D Ultrasound Prenatal Facial Landmark Detection
- • [PIPPI] Self-Tuning Age-Conditioned Choroid Plexus Segmentation in Neonatal MRI
- • [PIPPI] STORK: Spatio-Temporal Observation of uterine contRactions via neural networKs
- • [PIPPI] Shift functions with a spatial block bootstrap for within-subject comparison of placental T2* distributions under maternal hypoxia in a nonhuman primate model
- • [PIPPI] Region-Wise Interpretable Neonatal Brain Age Prediction via Pretrained Segmentation-Guided Attention
- • [PIPPI] Automated Fetal Brain MRI Biometry in Healthy and Pathological Cases
- • [PIPPI] High-resolution postmortem MRI of the human infant brain: cortical reconstruction and anatomical parcellation
- • [PIPPI] cSVR: Convolutional Slice-to-Volume Reconstruction
- • [PedAItrics] PSCT-Net: Geometry-Aware Pediatric Skull CT Reconstruction via Differentiable Back-Projection and Attention-Guided Refinement
- • [PedAItrics] Latent Space Oversampling for Adult–Pediatric Imbalance in Brain Tumor Segmentation
- • [PedAItrics] Privacy-Preserving Federated Distillation of Foundation Models for Multi-Institutional Pediatric Glioma Recurrence Prediction
- • [PedAItrics] Task-Aware Modality Contribution Fusion Framework for Pediatric Postoperative Gross Tumor Volume Segmentation
- • [PedAItrics] Growth modelling of children’s ear canals using implicit neural distance representations
- • [PedAItrics] Radiomic Prediction of Chronic Kidney Disease Progression in Children with Posterior Urethral Valves
- • [PedAItrics] Region-Wise Age Progression in Disentangled VAEs for 3D Face Meshes
- • [PedAItrics] Cross-cohort Transfer for Label-efficient Neonatal HIE Lesion Segmentation with Weak Supervision and Pseudo-normative Spatial Priors
- • [PedAItrics] Do Medical Vision-Language Models Work for Children? Evaluating MedGemma on Pediatric Pneumonia
- • [PedAItrics] Sequence-Agnostic MRI Segmentation of Pediatric Renal Tumors for Postoperative Flank Irradiation
- • [PedAItrics] Modeling Cardiac Normality for Neonatal CHD Screening on a Portable Single-View Device: Challenges of a Small-Sample Pediatric Pilot
- • [PedAItrics] Data-Efficient Pediatric Demyelinating Lesion Segmentation with Cross-Age Lesion Augmentation and Trustworthy Predictions
- • [PedAItrics] Transformer-Based Manifold Modeling of Novel Image Quality Metrics For Pediatric Brain MRI
-
• [PedAItrics] Enhancing Clinically-relevant Quality Control Through Automated Segmentation Performance Prediction
- Laslo, Daria; Strijbis, Victor IJ; Haddadi Avval, Atlas; Vogt, Franziska; Fathi Kazerooni, Anahita; Jiang, Zhifan; Parida, Abhijeet; Kann, Benjamin; Linguraru, Marius George; Franson, Andrea; Müller, Sabine; Rauschecker, Andreas M.; Jutzeler, Catherine R.; Brüningk, Sarah;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [PedAItrics] Ordinal regression of Robarts histopathology index for pediatric inflammatory bowel disease
- • [REG2026] Schema-Guided Tree-Structured Reasoning for Whole-Slide Pathology Workflows
- • [REG2026] Decoupling Structure from Perception: A Deterministic-DAG Report Generator with Leak-Fair Cross-Site Recognition for Computational Pathology
- • [REG2026] Slide-Impression-Guided Modular Reasoning for Pathology Report Generation
- • [REG2026] Multi-Scale MIL and Multi-Modal Large Language Modeling for Pathology Workflow Reasoning and Visual Grounding
- • [REG2026] SlotPath: Structured Slot Prediction and Retrieval for Reasoning-Guided Pathology Reporting
- • [REG2026] PathChain: Reproducing the Pathologist’s Diagnostic Workflow from Whole-Slide Images
- • [REG2026] Grounded Ontology Walker: Interpretable Diagnostic Reasoning and Report Generation for Whole Slide Images
- • [REG2026] Diagnosis-Conditioned Retrieval for Structured Pathology Workflows
- • [REG2026] Diagnostic Pathology Reporting and Reasoning via Autoregressive and Retrieval-Based Chain-Of-Thought
- • [REG2026] PRG-RGen: Pathologist Reasoning-Guided Report Generation on WSIs via Multimodal LLMs
- • [REG2026] Decomposing Whole Slide Image Report Generation with Graph-Constrained Multiple Instance Learning Workflows
- • [REG2026] A Branch-Aware, Confidence-Gated Reasoning Framework for Whole Slide Images
- • [REG2026] Diagnosis-Grounded Structured Decoding for Pathologist Reasoning-Trajectory and Report Generation
- • [REG2026] Graph-Constrained Visual Grounding for Pathology Reasoning
- • [REG2026] Ensembled Foundation-Model Pipeline for Reasoning-Guided Pathology Report Generation: A REG2 Challenge Submission
- • [REG2026] Reporting Without Generating: Retrieval-Based Chain-of-Thought Answering for Pathology
- • [REG2026] Structured Context Rendering for Consistent Pathology Workflows and Reports from Whole-Slide Images
- • [REG2026] Reasoning as Retrieval: Template-Grounded Chain-of-Thought Report Generation from Whole-Slide Images
- • [REG2026] Faithful Per-Task Attention for Chain-of-Thought Whole-Slide Pathology Report Generation
- • [RHEUM-AI] RASH: Rheumatoid Arthritis Synthetic Hand Dataset for Joint-Level Inflammation Estimation
- • [RHEUM-AI] Augmenting the Grey Zone: Generative Models for Ambiguous Kellgren–Lawrence Grade Boundaries in Knee Osteoarthritis
- • [RHEUM-AI] Prototypical Severity Representation Learning for Automated Calcium Pyrophosphate Deposition Disease Assessment
- • [RHEUM-AI] Ordinal DINOv2 Transfer for Joint-Level SvdH Scoring: What Helps and What Does Not
- • [RHEUM-AI] Why Isolated Joint Views Limit Bone-Erosion Segmentation on Hand Radiographs
- • [RHEUM-AI] Towards Multi-Task Ordinal Grading of Knee Osteoarthritis and Calcium Pyrophosphate Deposition Using Vision Foundation Models
- • [RHEUM-AI] Advantages and limitations of applying ML techniques in medical data analysis, illustrated with X-ray imaging
- • [RHEUM-AI] Interpretable Counterfactual Simulation of Knee Osteoarthritis Progression from qMRI Biomarkers
- • [RIME] TriFusion-SR: Joint Tri-Modal Medical Image Fusion and SR
- • [RIME] DenOiS: Dual-Domain Denoising of Observation and Solution in Ultrasound Image Reconstruction
- • [RIME] End-to-end Adaptive k-space Sampling, Reconstruction and Registration for Dynamic MRI
- • [RIME] Self-Supervised Multi-Contrast MRI Reconstruction via Permutation-Driven Contrast Invariance
- • [RIME] A Hierarchical Patch-wise Wavelet Loss for High-Frequency Detail Preservation in Accelerated MRI Reconstruction
- • [RIME] FetalSense: Anatomy-Guided Fetal–Probe Motion Disentanglement in Freehand Ultrasound
- • [RIME] An Anatomy-Driven Thoracic Respiratory Motion Model with Population-Calibrated Presets
- • [RIME] Adaptive Prior-Guided Cold Diffusion for Accelerated MRI Reconstruction
- • [RIME] Generative Priors for Total-Body PET Reconstruction
- • [RIME] Physics-Guided Noise2Noise Plug-and-Play MBIR for Ultra-Low-Dose CT Reconstruction
- • [RIME] CUPA-T2*: Covariance-Aware Uncertainty Propagation and Alignment for T2* Mapping in Accelerated MRI
- • [RIME] 3D Multi-Coil Brain MR k-Space Dataset for Deep Learning-Based Undersampled Reconstruction
- • [RIME] Domain-Adapted Bi-Planar RAFT for Dense 3D Cardiac Motion Estimation
- • [RIME] STUNet: A Spatiotemporal Deep Learning Approach for 7T fMRI Denoising
- • [RIME] Contrast-Reversal Augmentation for Adult-to-Neonatal MR Image Reconstruction: Pretraining and Fine-Tuning Strategies
- • [SAFER] When Adaptation Hurts: Connecting Representational Drift to OOD Failures in MedSAM Fine-Tuning
- • [SAFER] MeVisQA: Medical Visual Question Answering via Visual Programming
- • [SAFER] Few-Shot Concept Prompt Learning for Segmentation Foundation Models via Visual Grounding
- • [SAFER] Faithful Reasoning, Not More Reasoning: Chain-of-Thought Ablation for Tuberculosis Findings in Indonesian Chest X-Rays
- • [SAFER] CORTEX: A Structured Reasoning Benchmark for Trustworthy 3D Chest CT MLLMs
- • [SAFER] Priors Over Pixels: Present-Bias in Organ-Presence Grounding for Medical VLMs
- • [SAFER] Robustness Evaluation of Surgical Medical Visual Question Answering Models Under Textual Perturbations
- • [SAFER] EviCal-RR: Evidence-Calibrated Reasoning for Contactless Respiratory Monitoring
- • [SAFER] CADRE: Stable, Parameter-Efficient Adaptation of Medical Vision-Language Models with Bounded Forgetting and Prior Drift
- • [SASHIMI] RAFM: Retrieval-Augmented Flow Matching for Unpaired CBCT-to-CT Translation
- • [SASHIMI] DRIFT: Dual-Distillation Reference-Free One-Step Image Flow for Brain MRI Through-Plane Super-Resolution
- • [SASHIMI] nnDiffusion: A Standardized 3D Diffusion Framework for Medical Image Synthesis
- • [SASHIMI] Compositional Cross-Modality Translation via Whole-Volume Multitask Latent Flow Matching
- • [SASHIMI] ∆-Diffusion: Modeling Longitudinal Brain Amyloid-PET Trajectories via Conditional Poisson Diffusion Bridge
- • [SASHIMI] Few-Shot Flow Matching with Stochastic Barycentric Sampling for Image Synthesis
- • [SASHIMI] SymmAdapt: Symmetrical Flow Matching for Source-Free Domain Adaptation in Medical Image Segmentation
- • [SASHIMI] MedPCFM-TED: One-Step Point Cloud Flow Matching for Implant Generation via Teacher-Guided Endpoint Distillation
- • [SASHIMI] Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces
- • [SASHIMI] CONFLUX: A Latent Diffusion Model for 3D Chest-CT Synthesis with RL Post-Training
- • [SASHIMI] CytoSyn: a Foundation Diffusion Model for Histopathology Image Synthesis
- • [SASHIMI] Synthesizing CT-based Functional Lung Ventilation Map: A Comparative Study of Generative Models for Image-to-Image Translation
- • [SASHIMI] Regulate, Modulate, Differentiate: Towards Modelling Subtle Changes in Longitudinal Multiple Sclerosis MRI
- • [SASHIMI] OTLesMix: Wasserstein Barycenter and Optimal Transport Map for Synthetic Lesion Generation with Diverse Shapes and Locations
- • [SASHIMI] Beyond Visual Realism: The Neuro-Fidelity Index for Validating Geometric Integrity in Synthetic Brain MRI
- • [SASHIMI] Reverse Spatio-Temporal Disease Progression Modelling
- • [SASHIMI] Any-to-One CT Kernel Conversion without Source-Kernel Data
- • [SASHIMI] Uncertainty-Aware 3D Residual Wavelet Diffusion for Ultra Low-Field MRI Super-Resolution
- • [SASHIMI] SonoSPADE: Real-Time, Per-Tissue Ultrasound Texture Synthesis for Closed-Loop Acquisition
- • [SASHIMI] DisMorph: learning to disentangle technical distortions from true biological change
- • [SASHIMI] Sample Structure, Refine Contrast: Zero-Shot MR Image Harmonization with a Phase-Preserving Diffusion Prior
- • [SASHIMI] Relative Loss Balancing for High-Fidelity Synthetic CT Generation in the Abdomen
- • [SASHIMI] LoRCA: LoRA Cycle Adaptation for Histology to HiP-CT Translation with DINOv3
- • [SASHIMI] Does FLAIR super-resolution erase or hallucinate small white-matter lesions?
- • [SASHIMI] A Latent Single-Step Network is Sufficient for Accurate CBCT-CT Translation
- • [SASHIMI] From Undersampled to Diagnostic: Flow-Translated Embeddings for Knee Pathology Classification in Accelerated MRI
- • [SASHIMI] Virtual Patients, Real Gains: Simulated CT from Digital Twins for Multi-Task Lung Nodule Analysis
- • [SASHIMI] MRIComp4Flow: Compression of 3D Brain MRI for Training Multi-Modal Generative Models
- • [SASHIMI] WAND-CXR: A Morphometric Wasserstein Metric for Evaluating Anatomical Plausibility in Synthetic Chest Radiographs
- • [SASHIMI] Synthetic training for long-tail haemorrhagic lesion segmentation in data-scarce settings
- • [SASHIMI] Realistic Synthetic Data for Annotation-Free Pretraining in Liver Vasculature Segmentation
- • [SASHIMI] RECON: Restoration-Guided Conditioning for Thin-Structure-Coherent CT Super-Resolution
- • [SASHIMI] AxonSynth: Domain-Randomized Synthetic Data for Zero-Shot 3D Axon Segmentation in Light-Sheet Microscopy
- • [SASHIMI] Discovering Subtypes of Neurodegenerative Progression with a Scalable Connectome-Constrained Dynamic Model
- • [SASHIMI] Synthetic Data Augmentation via Stable Diffusion for Polyp Characterisation in Colon Capsule Endoscopy
- • [SASHIMI] Simulating the Radiological Appearance of Focal Cortical Dysplasia in MRI
- • [STACOM] FDW-Net: Frequency-Decoupled Wavelet Network for Atrial Segmentation in Cardiac MRI
- • [STACOM] MR-JEPA: A General Purpose Video Foundation Model for Cardiac MRI
- • [STACOM] Generative Brownian Bridge Diffusion In Motion Space For Enhanced Myocardial Strain Analysis
- • [STACOM] No Image, No Problem: End-to-End Multi-Task Cardiac Analysis from Undersampled k-Space
- • [STACOM] MoE-based Feature Adapter for Prompt-free Binary Coronary Artery Segmentation in X-ray Angiography Videos
- • [STACOM] Conditional 3D Shape Synthesis of the Left Atrial Appendage via Discrete Latent Diffusion
- • [STACOM] Learning from Acquisition: Metadata-driven Multimodal Pre-training for Cardiac MRI
- • [STACOM] Cardiac MRI Through-Plane Super-Resolution Guided by Reference and Memory
- • [STACOM] IVUS Plaque Characterization Descriptors Carry FFR Information Beyond Morphology in Borderline Lesions
- • [STACOM] Silent Failures of Right-Ventricular Ejection Fraction at High Segmentation Overlap: Evidence from Multi-Vendor Cardiac MRI
- • [STACOM] TSPFN: A Temporal Tabular Foundation Model for Physiological Time Series Classification
- • [STACOM] Automated Reconstruction of Patient-Specific 3D Bi-Atrial Meshes from Sparse 2D Cine CMR
- • [STACOM] Beyond Volume Overlap: Surface Matching for Topology-Aware Coronary Artery Segmentation
- • [STACOM] TT3D: Triangular Transport for 3D Left Ventricle Reconstruction
- • [STACOM] Same Branches, Different Trees: A Bifurcation Connectedness Metric for Coronary Artery Segmentation and FFR-CT Decision Agreement
- • [STACOM] Beyond the Left Atrium: Joint Generative Modeling of Bi-Atrial Anatomy
- • [STACOM] Physics-Informed Implicit Neural Representations for Improved Myocardial Perfusion MRI Quantification
-
• [STACOM] ORION-CMR: On-scanner Reporting with Integrated Foundation Model for End-to-End Cardiac MRI Analysis and Interpretation
- Demirel, Omer Burak; Horst, Kelly K.; Perazzolo, Alessio; Bruno, Elisa; Kaya, Kenan; Ouyang, Rongzhen; Ahmed, Enas; Smink, Jouke; Waddle, Spencer L.; Chao, Tzu Cheng; Wang, Dinghui; Langer, Steve G.; Kline, Timothy L.; Korfiatis, Panagiotis; Browne, Jacinta; Isgum, Ivana; Leiner, Tim;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [STACOM] Bi-PT: Bidirectional Cross-Attention Point Transformers for Four-Chamber Heart Reconstruction from Sparse Cardiac MRI Data
- • [STACOM] ECG-Based Prediction of Patient-Specific Myocardial Conduction Velocity with Electroanatomical Mapping Supervision
- • [STACOM] SynSeq: End-to-End SYNTAX Score Prediction from Coronary Angiography Videos
- • [STACOM] GeodVessel: A Geodesic Cost-Map Framework for Refining Coronary Vessel Connectivity
- • [STACOM] Physiology-Aware Graph Attention for Early Ventricular Reentry Prediction
- • [STACOM] 3D Left Ventricular Modelling and Quantification from 2D Echocardiography Using Automated View Positioning
- • [STACOM] Beyond MSE: Rician Likelihood Denoising for Self-Supervised Cardiac T2 and T1ρ MRI
- • [STACOM] A Neural Implicit Cardiac Atlas with Clinically Readable Subject Embeddings
- • [STACOM] GRC-ProbNet: Uncertainty-aware feature extraction for cardiovascular disease classification
- • [STACOM] Integrated CT-derived left atrial digital twins reveal complementary thrombogenic and arrhythmogenic substrates in atrial fibrillation
- • [STACOM] Multi-Stage Vascular Deformation Mapping in Extracranial Carotid Aneurysms
- • [STACOM] Myocardial Strain Drift Correction in Deep Learning Based Ultrasound Tracking
- • [STACOM] MyoUV: Learning Canonical UV Surface Fields for Sparse SAX Myocardial Reconstruction
- • [STACOM] Uncertainty Quantification in Cardiac Model Personalisation from Ultrafast Ultrasound
- • [STACOM] Cardiac Shape-Derived Endophenotypes and Covariant Correction using Statistical Motion Atlases
- • [STACOM] ViPS-FSL: Virtual-Patient Densification via Latent Space Co-Translation for Robust Few-Shot Cardiac MRI Segmentation
- • [STACOM] Beyond In-Distribution Metrics: A Systematic Out-of-Distribution Evaluation of Congenital Heart Disease Segmentation
- • [STACOM] Spatiotemporal Distillation via Recurrent Bottlenecks for Aortic Tracking
- • [STACOM] Automated Detection and Shape Analysis of Mitral Valve Prolapse and Annular Disjunction in the UK Biobank
- • [STACOM] Characterising cardiac tissue properties with graph neural networks
- • [STACOM] Deep Learning Helix Angle Estimation via Rule-based Pre-training and cDTI Fine-tuning
- • [STACOM] Continuous Volumetric Cardiac Motion Modelling for Analytical Derivatives from Cine MRI
- • [SWITCH] X-LMC: Cross-View Spatiotemporal Collateral Circulation Scoring from DSA
- • [SWITCH] Machine Learning for Stroke Outcome Prediction: Comparing Tabular Models to Clinical Scores on IST
- • [SWITCH] PROFIT: Prototype-Guided Few-shot Inference and Transfer for Multimodal Stroke Diagnosis
- • [SWITCH] VesselBridge3D: A Foundation Model Adaptation Framework for Label-Efficient 3D Vessel Segmentation
- • [SWITCH] Automated Distinction of Intimal and Medial Intracranial Arterial Calcification from CT Head
- • [SWITCH] Projection-Based Quality Assessment of Cerebrovascular Segmentations
- • [SWITCH] Arterial Change Detection in Cerebral Digital Subtraction Angiography
- • [SWITCH] Territory-Coupled Foundation Model Adaptation for ASPECTS Scoring on Non-Contrast CT
- • [SWITCH] Decoupled Node Localization and Edge Assignment for Vascular Graph Reconstruction
- • [SWITCH] Infarct Core Segmentation on Spectral CT Angiography using a Data-Uncertainty-Aware U-Net
- • [SWITCH] Contrastive Alignment and CT-Guided Distillation for Ultrasound-Only Intracerebral Hemorrhage Screening
- • [SWITCH] An Automated Framework for Synthetic Neurovascular Fluoroscopy Generation and Stent Retriever Segmentation
- • [SWITCH] Uncertainty-Guided Hierarchical Textual Modeling for Perivascular Space Segmentation
- • [SWITCH] An Imaging-Informed Reaction-Diffusion Model of Infarct Growth
- • [SWITCH] Area-guided latent coherence for post-hoc segmentation quality assessment in stroke imaging
- • [ShapeMI] AutoFFS: Adversarial Deformations for Facial Feminization Surgery Planning
- • [ShapeMI] Exploring the Influence of Prenatal Alcohol Exposure on Face Shape and Brain Development
- • [ShapeMI] Landmark Detection Supported by Anatomy Segmentation and Geometric Constraints
- • [ShapeMI] Learning to Reconnect: Graph-based Path Classification for Restoring Retinal Vessel Segmentation Connectivity
- • [ShapeMI] On the Viability of Semi-Supervised Segmentation Methods for Statistical Shape Modeling
- • [ShapeMI] Spherical RePaint: Label-Reusable Diffusion-Based Augmentation for Parcellation
- • [ShapeMI] SPVR: Explicit Shape-Prior-Guided 3D Vertebral Reconstruction from Orthogonal Projections
- • [ShapeMI] Mind the Gap: Mesh-Guided Repair of Broken Vessels
- • [ShapeMI] A Joint 2D–3D Statistical Shape Model for Orthopedic Reconstruction
- • [ShapeMI] VessComNet: Geometry-Aware 3D Vessel Completion Across Non-Contrast and Contrast-Enhanced CT Images
- • [ShapeMI] What Does Anatomical Shape Know About You? A Multi-Organ, Shape-Only Study of Demographic Prediction, Attribution, and Privacy
- • [ShapeMI] Predicting the Progression of Adolescent Idiopathic Scoliosis
- • [ShapeMI] Deep Shape Regression for Planar Curves with Multimodal Covariates
- • [ShapeMI] ZODIAC: Zero-shot Octree-based Diffusion for Anatomical Completion
- • [ShapeMI] Segmentation and keypoints transfer for volumetric medical shapes via functional maps
- • [ShapeMI] PanVasc: A Shape-Aware Framework for Peripancreatic Vascular Invasion Assessment in Pancreatic Ductal Adenocarcinoma
- • [ShapeMI] Extending the Evolutionary Skeletal Representation to the Cerebral Cortex Anatomy
- • [ShapeMI] BlendNet: on the Importance of Accurate Local Pre-Registration in the Image Registration Task
- • [ShapeMI] Medial Skeletons for Haustral Fold Detection in Colonoscopy
- • [ShapeMI] Learning the Marfan Face: A Conditional Mesh VAE for Explainable Screening and Synthetic Generation
- • [ShapeMI] Disentangled Geometric Variational Learning of Normative Pediatric Development from Anatomical Surface Representations of Patients with Pathology
- • [ShapeMI] Cardiac Shape Priors for Equivariant Neural Field Representations of Cine MRI
- • [ShapeMI] TRACE: Artifact-Robust Statistical Shape Modeling from Imperfect Surface Scans - A Case Study in Craniosynostosis 3D Photography
- • [ShapeMI] DINE: Distance Is Not Enough Learning Global Deformation Priors for Robust Soft-Tissue Point Cloud Registration
- • [ShapeMI] Interpretable Obstructive Sleep Apnea Screening from MRI-Derived Upper-Airway Surface Morphology with Class Node Graph Attention Networks
- • [ShapeMI] KneeFlow: A Flow Matching Framework for Patient-Specific Knee Reconstruction
- • [ShapeMI] Multiscale Wave-Shaping Neural Encoding with Cross-Attention Networks for 3D Organ Reconstruction and Generation
- • [ShapeMI] Rethinking Sequence Modeling on Cortical Surfaces: Robustness, Spatial Ordering, and Resolution in Infant Brain Age Prediction
- • [ShapeMI] An Implicit 3D Face and Palate Shape Model for Infant Orofacial Clefts
- • [ShapeMI] NO2SSM: A Discretization-Invariant Neural-Operator Approach to Statistical Shape Modeling
- • [ShapeMI] Learning To Focus: Anatomy-Guided Attention Regularization for Medical Image Classification
- • [ShapeMI] Predicting Brain Morphometry with MT-GNN: Mesh Evolution in Continuous Time with Graph-Based Metric Tensor Embeddings
- • [ShapeMI] Machine learning on subcortical brain features: A study of sample size efficiency for neurodegenerative disease classification
- • [ShapeMI] Mixture of Experts for Fine-Grained Shape Refinement in Medical Segmentation
- • [ShapeMI] SCALP: Semi-Supervised Statistical Shape Modeling from Imperfect 3D Photogrammetry via Landmark-Anchored Spectral Warping
- • [SynthOCT] SynthOCT Challenge: Introduction and Brief Overview
- • [SynthOCT] Speckle-Phase Refinement on an Exact Differentiable Scanner Twin for Inverse OCT Phantom Generation
- • [SynthOCT] Phase-Pair Holographic Inversion for OCT Digital Phantom Synthesis
- • [SynthOCT] Coherent Differentiable Inversion for High-Fidelity Digital Phantom Generation in Optical Coherence Tomography
- • [TIA] Quantification of Parenchymal Abnormalities Using a Statistical Model of Lung CT Density
- • [TIA] Cupido Loss for Structure-Aware Pulmonary Airway and Artery Segmentation
- • [TIA] PE-QUEST: QUality ESTimation-driven Sample Selection for Pulmonary Embolism Segmentation
- • [TIA] CT-CLIP Representations for Multimodal Lung Cancer Survival Prediction
- • [TIA] Pulmonary Artery-to-Aorta Ratio Estimation via Landmark-Guided Orthogonal Slicing
- • [TIA] Big, Bright, or Invisible: A Frozen-Feature Benchmark of 3D CT Foundation Models
- • [TIA] Ordinal deep learning for pulmonary nodule risk assessment: an external validation study on a novel screening cohort
- • [TIA] Anatomy-Aware MAE Pretraining for Generalizable Coronary Artery Segmentation
- • [TIA] Comparison of intensity, transformation, and hybrid non-contrast CT ventilation methods for discriminating health from obstructive lung disease
- • [TIA] 3D-4C-SegNet: Four-Chamber Segmentation and LVEF Calculation in 4D Echocardiography
- • [TIA] TrICON: Learning Diffeomorphic Lung CT Registration through Triplet Consistency
- • [TIA] Interpretable Region-wise Gated CT–Ventilation Fusion for FEV1 Prediction in COPD
- • [TIA] X2V: Deformable 2D/3D Registration from Intraoperative X-ray to Volume via Motion Manifold Learning
- • [TIA] Prompt-Guided Interactive Segmentation of Interstitial Lung Disease in Thoracic CT
-
• [TIA] An automated segmentation model for Mucus Plug quantification in Chest CT
- Wang, Shanshan; McCabe, John; Chen, Yunjie; Azimbagirad, Mehran; Vasudev, Pardeep; Baxter, Gabrielle; Lim, Jason; Zahid, Azib; Egashira, Ryoko; Szmul, Adam; Yang, Tianqi; Cheng, Daryl; Kinney, Greg L.; Callister, Matthew E. J.; Lynch, David A.; Janes, Sam M.; Alexander, Daniel C.; Jacob, Joseph;
- [PDF] [Paper Information and Reviews] [bibtex]
- • [TIA] Prompt-Guided Target-Lesion Segmentation of Infectious Pulmonary Nodules: Model Benchmarking and Localization-Effort Analysis
- • [TIA] Deep Learning for UIP Detection in HRCT Scans: A Comparative Evaluation of Input Representations, Feature Extractors, and Aggregation Strategies
- • [TIA] Deep Learning Correction of Respiratory Motion Artifacts in 4DCT
- • [TIA] ARC-CT: Anatomy-Routed Contrastive Vision-Language Learning for 3D Chest CT
- • [TIA] Deep Learning Classification for Rare Pulmonary Infection Differentiation in Immunocompromised Patients: A Data-Limited Study
- • [TIA] Generic or Domain-Specific? Foundation Models for Annotation-Efficient ILD Segmentation
- • [TIA] Minimum-Cost Path Framework for 3D Airway Centerline Extraction
- • [TIA] Deep Learning-Based Synthesis of Hyperpolarized Gas MRI Lung Ventilation from Multi-Inflation Proton MRI: A Comparison of CNN, GAN and Transformer Architectures
- • [TIA] Scene-Graph Contrastive Pretraining with Concept-Based Hard Negatives for Radiology Report Generation
- • [TIA] Multimodal Routing and Region Refinement for Language-Guided Medical Image Segmentation
- • [TREAT-MMTB] CaviFusionNet-T1: A Multi-Branch Ensemble for Pulmonary Cavity Detection and Segmentation in the TREAT-MMTB 2026 Challenge
- • [TREAT-MMTB] Detection-Gated Cavity Segmentation on Chest X-rays with Vision–Language Pretraining
- • [TREAT-MMTB] Generalizable Tuberculosis Classification on Chest X-rays through Multi-Source Curation and Model Ensembling
- • [TREAT-MMTB] Class-Weighted Metadata-Aware Ark+ Fusion for Multimodal Tuberculosis Classification
- • [TREAT-MMTB] Morphology-Informed Deep Ensemble Learning for Pulmonary Cavity Detection and Segmentation on Chest X-Rays
- • [TREAT-MMTB] GO-CavNet: Ordinal-Supervised, Detection-Gated Cavity Segmentation for Tuberculosis Chest Radiographs
- • [TREAT-MMTB] MOPH AI: Cross-Modality Paired MixStyle for Tuberculosis Classification in TREAT-MMTB 2026
- • [TREAT-MMTB] Global-to-Local Segmentation and Context-Aware Detection of Tuberculosis Cavity in Chest X-rays
- • [TREAT-MMTB] Domain-Aware Tuberculosis Screening with a LoRA-Adapted Chest X-Ray Foundation Model
- • [TREAT-MMTB] RADAR: Acquisition-Adversarial Attention Pooling over a Frozen Chest-Radiograph Foundation Model for Tuberculosis Screening
- • [TREAT-MMTB] Prevalence-Aware Rank Fusion for Tuberculosis Cavity Detection and Segmentation
- • [TopAneu] Anatomy-Aware Intracranial Aneurysm Analysis with Vessel-Guided Dual-Decoder Multi-Task Learning
- • [TopAneu] VaMosV2: A Multi-step Procedural Model That Generates Full 3D Synthetic MRA Volumes for Data Augmentation in the TopAneu ICA Segmentation Challenge
- • [TopAneu] Vessel Segmentation and Anatomically Informed Rule-Based Localization of Intracranial Aneurysms
- • [TopAneu] An Anatomy-Aware Staged Pipeline for Vessel-Specific Intracranial Aneurysm Segmentation in CT and MR Angiography
- • [TopAneu] Vessel-Aware Multi-Task 3D U-Net for Vessel-Specific Intracranial Aneurysm Classification and Segmentation
- • [TopAneu] Vessel-Guided Aneurysm Localization and Segmentation for TopAneu 2026
- • [UNSURE2026] When Does Prompt-Perturbation Uncertainty Catch Interactive-Segmentation Failures? An Empirical Study on SAM/MedSAM
- • [UNSURE2026] Beyond Dice: A Reliability-Oriented Evaluation of Geometric Test-Time Augmentation in Medical Image Segmentation
- • [UNSURE2026] From Generation to Decision: Structure-Aware Reliability for Cardiac MRI Reporting
- • [UNSURE2026] Reliability, Not Accuracy, Is the Bottleneck in AI-assisted Post-Treatment Glioma Segmentation: Region-Aware Recalibration and Risk-Controlled Triage
- • [UNSURE2026] Image Segmentation Calibration Based on Estimated Segmentation Quality
- • [UNSURE2026] Not All Errors Are Equal: Threshold-Aware Loss Functions for Opportunistic Osteoporosis Screening
- • [UNSURE2026] Geometric Diversity: Mixed-Curvature Heads as a Substitute for Ensemble Independence
- • [UNSURE2026] Bound-Aware Per-Organ Recall Risk Control for Multi-Organ CT Segmentation under Clinical Domain Shift
- • [UNSURE2026] Subgroup-Dependent Report-Label Noise Distorts Fairness Audits of Chest X-ray Classifiers: A Prediction-Powered Correction
- • [UNSURE2026] Uncertainty Estimation in Deep Learning MRI Reconstruction with Focus on Pathologies
- • [UNSURE2026] Beyond Morphological Dilation: Revisiting Conformal Prediction for 3D Tumor Segmentation
- • [UNSURE2026] Example-based Explainable Selective Classification with Graph Neural Networks for Urinary Sediment Examination
- • [UNSURE2026] Beyond Boundary Noise: Aggregated Aleatoric Uncertainty Fails to Capture Presence Ambiguity in 3D Lung Nodule Segmentation
- • [UNSURE2026] Evaluating and Calibrating Diffusion Model-derived Uncertainty for Quantitative MRI Mapping
- • [UNSURE2026] Improving Calibration of Black-Box Radiology AI Using Test-Time Augmentation
- • [UNSURE2026] Well-Calibrated but Unusable: Calibration Error Does Not Certify Zero-Shot Chest X-Ray VLMs
- • [UNSURE2026] Uncertain but Useful: Leveraging CNN Training Variability into Data Augmentation
- • [UNSURE2026] Does Inter-Rater Variability Matter? Preclinical MRI Tumor Segmentation and Downstream Analysis
- • [UNSURE2026] A Principled Approach to Unsupervised Anomaly Detection
- • [UNSURE2026] Counterfactual Marginalisation: Framework for Evaluating Robustness to Nuisance Variables
- • [UNSURE2026] Foundation Model and Radiomics Distance Scores for Post-Hoc Segmentation Failure Detection
- • [UNSURE2026] Beyond Uncertainty: Generalizable Failure Monitoring for Surgical Segmentation under Acquisition Degradation
- • [UNSURE2026] SegWithU: Deterministic Perturbation Probes for Single-Backbone-Pass Risk-Aware Medical Image Segmentation
- • [UNSURE2026] Layer Selection in VLMs for Zero-Shot OOD Detection via Multi-Resolution Entropy Estimation
- • [UNSURE2026] Uncertainty Identifies Difficult Samples Across Methods: A Multi-Task Study on a Heterogeneous Skin Lesion Dataset
- • [UNSURE2026] Confidence-Tiered Quality Control for Reliable Radiomic Biomarkers in Multicentre PET-CT
- • [UNSURE2026] Quantile regression enables reliable, uncertainty-aware endoscopic scoring in ulcerative colitis clinical trials
- • [UNSURE2026] Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection
- • [UNSURE2026] When Voxels Are Not Equal: Spacing-Driven Metric Bias and Metric Uncertainty in Segmentation
- • [UNSURE2026] Predictive Entropy as a Joint Screen for Error and Paraphrase Instability in Medical Vision-Language Models
- • [UNSURE2026] FetalEDL: OOD-Aware Evidential Deep Learning for Reliable Fetal Ultrasound Plane Classification
- • [UNSURE2026] Explanation Uncertainty in the Classification of Pulmonary Nodules
- • [UNSURE2026] Complementary Reliability Axes for Aortic CTA Segmentation: An Empirical Audit
- • [UNSURE2026] Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR
- • [UNSURE2026] Beyond Mean Uncertainty: Case-wise AUSE for Detecting Failures in 3D Pelvic Tilt Estimation from a Single AP Radiograph
- • [UNSURE2026] Sequential Conformal Safety for Trustworthy Clinical Decision Pathways in Ophthalmology
- • [UNSURE2026] Uncertainty-Aware Bone Age Assessment: Analysis of Conformal and Bayesian Methods
- • [UNSURE2026] Label-Free Threshold Selection for Out-of-Distribution Detection in Liver CT Segmentation
- • [cdmri] Experimental Study of the Impact of Virtual Reality on Fiber Bundle Editing and Annotation
- • [cdmri] Spatial Masked-Set Learning for Sparse Multi-Shell Diffusion MRI Signal Synthesis
- • [cdmri] AdaViT: Adaptive Viral Tracing Informed Tractography
- • [cdmri] DiffBench: A Benchmark Toward Reproducible Evaluation in Diffusion MRI Prediction
- • [cdmri] In-Plane Super-Resolution: A Feasibility Study
- • [cdmri] Towards Region-Agnostic Multi-Tissue Segmentation of Brain MRI: Application to Temporal Lobe Epilepsy Resections
- • [cdmri] Region-Specific Sample Size Requirements for Calibrated Normative Modeling of Diffusion Tensor Imaging Fractional Anisotropy Across the Lifespan
- • [cdmri] Quantitative R2 Estimation from Multi-Parameter and dMRI Measurements using Neural Networks
- • [cdmri] Segmentation-Conditioned Latent Diffusion for Prostate High-b-value DWI and ADC Synthesis
- • [cdmri] Topology-Aware Training and Spatial Diagnostics for Fiber Bundle Segmentation in Tracer Histology
- • [iMIMIC] Understanding Synergistic Interactions among Pathology Foundation Models via Adaptive Fusion
- • [iMIMIC] Cellular-Communication-Level Interpretability for Pathology Foundation Models via Graph Distillation on Microenvironment
- • [iMIMIC] A Probabilistic Source-Free Domain Adaptation Method for Concept Bottleneck Models
- • [iMIMIC] Retrieving Patient-Specific Radiomic Feature Sets for Transparent Knee MRI Assessment
- • [iMIMIC] RESHAPE: Representation Learning for the Explainability of Shapes
- • [iMIMIC] Spatial Message Passing in Language Space for Pathology Image Interpretation
- • [iMIMIC] Recursive Uncertainty-Gated Image Registration for Learning-Based Algorithms
- • [iMIMIC] How Well Do Chest X-Ray VLM Attention Overlays Match Radiologist Boxes? A Cross-Model Audit and Radiologist Reader Study
- • [iMIMIC] Less Annotation, More Interpretation: Prior-Guided Concept Bottleneck Models for Interpretable Cancer Imaging Diagnosis
- • [iMIMIC] Faithful Faithfulness Evaluations: Challenges & Pitfalls Learned from a Breast MRI Case Study
- • [iMIMIC] When Saliency Over-Credits Anatomy: Token-Level Evidence Flow in Frozen Medical Vision Transformers
- • [iMIMIC] Towards Interpretable Foundation Models for Retinal Fundus Images
- • [iMIMIC] Anatomical Information or Domain Shortcuts? Probing Image- and Shape-Based Embeddings in Ear CT with Landmark-Derived Features
- • [iMIMIC] SAGE: Semantic Explainability of Attention-Based Survival Models in Computational Pathology
- • [iMIMIC] P3CA: Encoder-Agnostic Interpretation of Vision Foundation Model Embeddings via Spatial Probing
- • [iMIMIC] Attention Without Grounding: Causal Evaluation of Visual Explanations in Medical VLMs