FLAIRBrainSeg: Fine-grained brain segmentation using FLAIR MRI only

• URL: http://arxiv.org/abs/2504.03376v1
• Date: Fri, 04 Apr 2025 11:47:18 GMT
• Title: FLAIRBrainSeg: Fine-grained brain segmentation using FLAIR MRI only
• Authors: Edern Le Bot, Rémi Giraud, Boris Mansencal, Thomas Tourdias, Josè V. Manjon, Pierrick Coupé,
• Abstract summary: This paper introduces a novel method for brain segmentation using only FLAIR MRIs.<n>By leveraging existing automatic segmentation methods, we train a network to approximate segmentations, typically obtained from T1-weighted MRIs.<n>Our method, called FLAIRBrainSeg, produces segmentations of 132 structures and is robust to multiple sclerosis lesions.
• Score: 0.5277756703318045
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This paper introduces a novel method for brain segmentation using only FLAIR MRIs, specifically targeting cases where access to other imaging modalities is limited. By leveraging existing automatic segmentation methods, we train a network to approximate segmentations, typically obtained from T1-weighted MRIs. Our method, called FLAIRBrainSeg, produces segmentations of 132 structures and is robust to multiple sclerosis lesions. Experiments on both in-domain and out-of-domain datasets demonstrate that our method outperforms modality-agnostic approaches based on image synthesis, the only currently available alternative for performing brain parcellation using FLAIR MRI alone. This technique holds promise for scenarios where T1-weighted MRIs are unavailable and offers a valuable alternative for clinicians and researchers in need of reliable anatomical segmentation.

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