SuCor：一种基于无参数自正则化最优传输的磁敏感畸变校正方法 / SuCor: Susceptibility Distortion Correction via Parameter-Free and Self-Regularized Optimal Transport
1️⃣ 一句话总结
这篇论文提出了一种名为SuCor的新方法，它利用最优传输理论自动校正脑部扫描图像中的几何畸变，无需人工调整参数，就能比现有主流方法更准确、更快速地使功能图像与结构图像对齐。
arXiv 提交日期: 2026-03-17
Abstract - SuCor: Susceptibility Distortion Correction via Parameter-Free and Self-Regularized Optimal Transport
We present SuCor, a method for correcting susceptibility induced geometric distortions in echo planar imaging (EPI) using optimal transport (OT) along the phase encoding direction. Given a pair of reversed phase encoding EPI volumes, we model each column of the distortion field as a Wasserstein-2 barycentric displacement between the opposing-polarity intensity profiles. Regularization is performed in the spectral domain using a bending-energy penalty whose strength is selected automatically via the Morozov discrepancy principle, requiring no manual tuning. On a human connectome project (HCP) dataset with left-right/right-left b0 EPI pairs and a co-registered T1 structural reference, SuCor achieves a mean volumetric mutual information of 0.341 with the T1 image, compared to 0.317 for FSL TOPUP, while running in approximately 12 seconds on a single CPU core.
源自 arXiv: 2603.16758