Abstract
Automated assessment of the Critical View of Safety (CVS) in laparoscopic cholecystectomy requires both recognition of the three CVS criteria and anatomical grounding in small, rare, and often occluded hepatocystic structures. Reliable grounding of this safety-critical anatomy remains the main bottleneck. We propose CasCVS-Net, a staged multi-task cascade that jointly performs object detection, semantic segmentation, and CVS assessment, trained on the Endoscapes dataset. The model couples the tasks through predicted anatomy: predicted boxes guide segmentation, and predicted masks provide region-level features for CVS classification. To reduce optimisation instability in this coupled setting, training progresses from detection through detection–segmentation to the full three-task cascade, followed by task-wise fine-tuning. Evaluation on the public unseen test set shows that CasCVS-Net improves over matched single-task baselines on all three tasks, achieving 32.0 detection mAP, 46.8 semantic mIoU, 15.3 rare-anatomy mIoU, and 67.2 CVS mAP. For CVS, our method achieves the best overall balance between mAP and bAcc, improving mAP over LG-CVS and SV2LSTG by 4.0 and 2.9 points, respectively, while achieving comparable mAP to SwinCVS with substantially higher bAcc (74.7 vs. 70.3). These results show that staged task coupling through predicted boxes and masks improves anatomical grounding for CVS assessment, particularly for rare hepatocystic structures.
Links to Paper and Supplementary Materials
Main Paper (Open Access Version): https://papers.miccai.org/miccai-2026-sat/paper/SafeSurg_011.pdf
SharedIt Link: Not yet available
SpringerLink (DOI): Not yet available
Supplementary Material: Not Submitted
Link to Open Review
Open Review Page: https://openreview.net/forum?id=0CzJNVWZmo
BibTex
@InProceedings{TohBoc_CasCVSNet_MICCAISAT2026,
author = { Toh, Bock-Zien AND Ren, Yuanchuan AND Yu, Tay Aw AND Ng, Khee Ong AND Mao, Zhehua AND Bano, Sophia},
title = { { CasCVS-Net: A Staged Multi-Task Cascade for Critical View of Safety Assessment } },
booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026 Workshops and Challenges},
year = {2026},
publisher = {Springer Nature Switzerland},
volume = {LNCS pending},
month = {pending},
page = {pending}
}