Abstract
The phase component of a magnetic resonance (MR) imaging signal stores important structural and biological properties of imaged tissues, but utilizing phase data requires preprocessing. Global phase wrapping occurs in most acquired MR signals, and subsequent phase unwrapping is NP-hard. This work presents a 3D phase unwrapping method using a series of iterative graph cuts. We propose a continuous optimization approach to solve for the optimal cut. The method achieves an average peak signal-to-noise ratio of $133.6$ on noisy phantom images and performs unwrapping faster than the state-of-the-art graph cuts approach. The code associated with this work is available at \url{github.com/katembartz/COOGAR}.
Links to Paper and Supplementary Materials
Main Paper (Open Access Version): https://papers.miccai.org/miccai-2026-sat/paper/GRAIL_017.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=B1KQR6ctmx
BibTex
@InProceedings{BarKat_AContinuous_MICCAISAT2026,
author = { Bartz, Kathleen M. AND Wei, Shuwen AND Remedios, Samuel W. AND Zhang, Jinwei AND Carass, Aaron AND Dewey, Blake E. AND Prince, Jerry L. AND Trzasko, Joshua D.},
title = { { A Continuous Optimization Approach for Graph Cuts-based Phase Unwrapping } },
booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026 Workshops and Challenges},
year = {2026},
publisher = {Springer Nature Switzerland},
volume = {LNCS 17278},
month = {pending},
page = {pending}
}