WMH Segmentation (Claude Skill)
Perform automated white matter hyperintensity (WMH) segmentation on structural MRI data using the MARS-WMH nnU-Net model.
| Type | Claude Skill |
| Supplier | CUHK-AIM-Group (community OSS, MIT) |
| Availability | GA — part of the NeuroClaw neuroimaging skill library |
| Pricing | Free / OSS (MIT) |
| Capabilities | Read/Write — Claude runs the skill’s Python locally (Bash), not as an MCP tool |
How to install
- Claude Code — clone and copy the skill into your skills directory:
git clone https://github.com/CUHK-AIM-Group/NeuroClaw cp -r NeuroClaw/skills/wmh-segmentation ~/.claude/skills/Project-scoped alternative: copy into
.claude/skills/instead. NeuroClaw skills assume the collection’s shared helpers (claw-shell, modality tool skills) and the upstream neuroimaging stack (FreeSurfer/FSL/fMRIPrep/etc.) — install those dependencies, or run the bundled installer for the full environment:cd NeuroClaw && python installer/setup.pywhich configures the Python env, CUDA/GPU, and the neuroimaging tools.
What it does
Use this skill whenever the user wants to perform automated white matter hyperintensity (WMH) segmentation on structural MRI data using the MARS-WMH nnU-Net model. Requires one FLAIR and one T1w NIfTI image (no contrast). Triggers include: ‘wmh’, ‘white matter hyperintensities’, ‘WMH segmentation’, ‘MARS-WMH’, ‘wmh-nnunet’, ‘segment FLAIR T1’, ‘white matter lesions’, ‘vascular WMH’, ‘mars wmh’, or any request to run nnU-Net WMH segmentation on FLAIR+T1w pair.
Primary use cases: ‘wmh’, ‘white matter hyperintensities’, ‘WMH segmentation’, ‘MARS-WMH’, ‘wmh-nnunet’, ‘segment FLAIR T1’, ‘white matter lesions’, ‘vascular WMH’, ‘mars wmh’, or any request to run nnU-Net WMH segmentation on FLAIR+T1w pair.
Notes
Distributed as a SKILL.md (plus code examples) in the NeuroClaw skill library — Claude executes it locally via Bash/Python rather than as an MCP server. Upstream license: MIT. The skill directory upstream is skills/wmh-segmentation.
Sources
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