SuCor: Susceptibility Distortion Correction via Parameter-Free and Self-Regularized Optimal Transport
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866911523311452160 |
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| author | Chigurupati, Sreekar Garyfallidis, Eleftherios |
| author_facet | Chigurupati, Sreekar Garyfallidis, Eleftherios |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_16758 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SuCor: Susceptibility Distortion Correction via Parameter-Free and Self-Regularized Optimal Transport Chigurupati, Sreekar Garyfallidis, Eleftherios Computer Vision and Pattern Recognition 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. |
| title | SuCor: Susceptibility Distortion Correction via Parameter-Free and Self-Regularized Optimal Transport |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2603.16758 |