Agent skill · Data & Analytics

wmh-segmentation

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.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill wmh-segmentation --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Requires: - claw-shell
Path: skills/neuroclaw/wmh-segmentation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# WMH Segmentation (MARS-WMH nnU-Net) ## Overview MARS-WMH is the state-of-the-art, clinically-validated deep-learning tool (nnU-Net architecture) for segmenting brain white matter hyperintensities of presumed vascular origin. It takes a FLAIR image (recommended 1 mm isotropic) and a co-registered or registrable T1w image (1 mm isotropic, no contrast) and outputs a precise WMH segmentation mask in NIfTI format (returned in the original input resolution). This skill serves as the **NeuroClaw interface-layer wrapper** for the official MARS-WMH Docker container (`ghcr.io/miac-research/wmh-nnunet:latest`) and strictly follows the hierarchical design: 1. Check whether Docker (with NVIDIA Container Toolkit) is installed (`docker --version` + `nvidia-smi` via `claw-shell`). 2. If `nvidia-smi` fails → immediately print the exact NVIDIA Container Toolkit installation commands and instruct the user to run them manually before retry. 3. If paths not provided → interactively ask the user for FLAIR and T1w full paths and confirm they exist on disk. 4. If paths provided → verify file existence and readability. 5. Prepare clean working directory, copy inputs, generate exact Docker pull/tag + run

What's inside
Steps it walks through
  1. Overview
  2. Quick Reference (Common Use Cases)
  3. Installation Check & Setup
  4. NeuroClaw recommended wrapper script
  5. Important Notes & Limitations
  6. When to Call This Skill
  7. Complementary / Related Skills
  8. Reference
Commands it runs
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | \
sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -fsSL https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#' | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list > /dev/null
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker
WMH Segmentation Shell Commands (execute via claw-shell)
More from awesome-bio-agent-skills
All skills →
report-templatePublication-quality PDF report generation using Typst templates. Produces professional scientific…Code Review & Qualitysec-reportSEC (size-exclusion chromatography) analysis with peak detection, oligomer classification, and…Code Review & Qualitybio-atac-seq-consensus-peaksetBuild a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative…Otherbio-toolsBiology research tools reference. Always available inside agent containers.AI & Agentsbio-remote-homologyDetect distant homologs using profile and structure-aware methods that go beyond standard BLAST.…Otherbio-variant-callingCall SNPs and indels from aligned reads using bcftools mpileup and call. Use when detecting…Other
About this skill
What does the wmh-segmentation skill do?

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.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill wmh-segmentation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going
All skills →
The full catalog, by category and by tool.
Open Source Radar →
The repositories these skills come from, watched daily.
The people behind them →
Makers and builders across the ecosystem.