Load and validate NIfTI files, inspect affines, and convert voxel coordinates.
npx skills add https://github.com/CUHK-AIM-Group/NeuroClaw --skill nibabel-skill
Please help me install this Agent Skill. Skill: nibabel-skill Source: https://github.com/CUHK-AIM-Group/NeuroClaw/tree/main/skills/nibabel-skill Command: npx skills add https://github.com/CUHK-AIM-Group/NeuroClaw --skill nibabel-skill
This skill provides a nibabel-based, low-level neuroimaging I/O toolkit for loading, validating, and manipulating NIfTI images and reading FreeSurfer geometry/annotations.
Demonstrate a nibabel workflow by loading a NIfTI, inspecting its shape and affine, and saving a derived image.
High-intent search queries and answers about installing and using this skill.
NIfTI affine inspection uses nibabel to load the image and return both the voxel array shape and the 4x4 affine matrix mapping voxel indices to world coordinates, enabling geometry validation for neuroimaging workflows.
Voxel-to-world coordinate conversion applies the NIfTI image's affine matrix to voxel indices, yielding spatial coordinates in the anatomical reference frame. This requires loading the NIfTI file with nibabel and numpy to perform the matrix multiplication.
Saving a modified NIfTI image uses nibabel to write a derived .nii copy preserving the affine header, while coordinate tables can be exported to CSV using pandas, generating structured outputs for downstream neuroimaging analysis.
Pandas is only required if you need to export coordinate or metadata tables to CSV format. Core NIfTI loading, shape validation, and affine inspection rely on nibabel and numpy, making pandas an optional dependency for data export tasks.
Validating NIfTI geometry involves loading the image with nibabel to check the shape against expected dimensions and inspecting the affine matrix for correct spatial orientation. This ensures atlas alignment before coordinate-based analysis.
CUHK-AIM-GroupTranslate neuroimaging outputs into publication-ready figures and 3D meshes.
Lord1EgyptAnalyze structural and functional neuroimaging data from fMRI and MRI modalities.
Hung-3008Parse FCS files into NumPy arrays with channel metadata and CSV export.
MarvinCuiPlan fMRI GLM, masking, connectome, and ML workflows in Python with Nilearn guidance.
