Native-Space 3D CarveMix for Multi-Site T1w Stroke Segmentation
Segmenting ischemic stroke lesions on T1-weighted (T1w) MRI acquired across different scanners and protocols without intensity standardization is difficult because lesions are subtle and share intensity characteristics with cerebrospinal fluid. Standard deep learning architectures trained across multiple centers plateau around Dice 0.66, with acute lesions ($\le 7$ days post-stroke) performing substantially worse due to severe sample scarcity. We combine a MedNeXt-L ($k=5$) backbone with on-the-fly 3D CarveMix augmentation that pastes real lesion patches into healthy brain regions during training. By generating synthetic lesion placements dynamically within each fold with subject-level sp...
| Authors | Dexter Wen Jie Teo, Kumaradevan Punithakumar |
|---|---|
| Primary category | eess.IV |
| Published | 24 August 2026 |
| Last updated at source | 24 August 2026 |
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