Extract diffusion MRI metrics from DWI data using DIPY.
npx skills add https://github.com/CUHK-AIM-Group/NeuroClaw --skill dipy-tool
Please help me install this Agent Skill. Skill: dipy-tool Source: https://github.com/CUHK-AIM-Group/NeuroClaw/tree/main/skills/dipy-tool Command: npx skills add https://github.com/CUHK-AIM-Group/NeuroClaw --skill dipy-tool
Diffusion MRI data processing is complex; this Skill provides a reusable DIPY-based foundation to load DWI data (NIfTI with bvals/bvecs), apply optional masking, fit diffusion tensors, and export diffusion metrics and ROI statistics for analysis.
Run the DIPY-based tensor metric workflow on a DWI dataset to generate FA, MD, AD, and RD maps alongside ROI statistics.
High-intent search queries and answers about installing and using this skill.
You can compute FA, MD, AD, and RD maps from DWI NIfTI data using DIPY by loading the raw data with corresponding bvals and bvecs, applying optional brain masking, fitting the diffusion tensor model, and saving the resulting metric maps as NIfTI images for downstream analysis.
The best way to extract diffusion MRI ROI statistics across subjects is to fit diffusion tensors to generate metric maps, then compute atlas-based ROI summaries and export the results as CSV files. This ensures reproducible diffusion metrics for neuroimaging research workflows.
Yes, you can apply a supplied custom brain mask when fitting diffusion tensors. If a mask is not provided, the workflow can automatically generate one using the median_otsu method before performing tensor fitting to obtain FA, MD, AD, and RD maps.
To process DWI data and export diffusion metrics, you need DIPY for diffusion tensor fitting, nibabel for loading NIfTI data, numpy for array operations, and pandas for exporting atlas-based ROI statistics as CSV summaries.
Yes, the workflow supports optional b-value filtering when loading raw DWI data. This allows you to exclude specific gradient directions or shells before brain masking and tensor fitting to ensure accurate FA, MD, AD, and RD metric calculation.
DWI NIfTI files fail shape validation when the image dimensions do not align with the provided bvals and bvecs. The workflow performs shape validation upon loading to ensure the DWI data matches the gradient table before applying masking and fitting diffusion tensors.
CUHK-AIM-GroupLoad and validate NIfTI files, inspect affines, and convert voxel coordinates.
CUHK-AIM-GroupTranslate neuroimaging outputs into publication-ready figures and 3D meshes.
CUHK-AIM-GroupPlan diffusion MRI preprocessing and metric extraction workflows across DICOM, NIfTI, and BIDS datasets.
HaoxuanLiTHUAISelect evidence-accumulation models for choice-response time data.
