FLAIRBrainSeg: Fine-grained brain segmentation using FLAIR MRI only

Edern Le Bot; Rémi Giraud; Boris Mansencal; Thomas Tourdias; Josè V. Manjon; Pierrick Coupé

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arXiv · 2504.03376

FLAIRBrainSeg: Fine-grained brain segmentation using FLAIR MRI only

Edern Le Bot·Rémi Giraud·Boris Mansencal·Thomas Tourdias·Josè V. Manjon·Pierrick Coupé

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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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Edern Le Bot, Rémi Giraud, Boris Mansencal, Thomas Tourdias, Josè V. Manjon, Pierrick Coupé. 2025-04-04. FLAIRBrainSeg: Fine-grained brain segmentation using FLAIR MRI only. https://arxiv.org/abs/2504.03376

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