Build automated pipelines for medical imaging data: format conversion (DICOM to NIfTI, PNG, HDF5), batch processing, ML dataset preparation, research data export, and imaging ETL workflows. Use when converting DICOM to other formats, preparing imaging datasets for machine learning, building research data pipelines, batch processing medical images, extracting imaging features, or automating imaging workflows.
Quickly install medical imaging pipelines AI skill to your development environment via command line
Source: aurabx/skills.
Generates code for end-to-end medical imaging data pipelines: ingestion, format conversion, preprocessing, dataset preparation, and export. Covers the common path from raw DICOM files to ML-ready datasets, research exports, and automated processing workflows.
NIfTI is the standard format for neuroimaging research (brain MRI, fMRI). Use SimpleITK for robust conversion that preserves spatial metadata.
Build automated pipelines for medical imaging data: format conversion (DICOM to NIfTI, PNG, HDF5), batch processing, ML dataset preparation, research data export, and imaging ETL workflows. Use when converting DICOM to other formats, preparing imaging datasets for machine learning, building research data pipelines, batch processing medical images, extracting imaging features, or automating imaging workflows. Source: aurabx/skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/aurabx/skills --skill medical imaging pipelines Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
Stable fields and commands for AI/search citations.
npx skills add https://github.com/aurabx/skills --skill medical imaging pipelinesBuild automated pipelines for medical imaging data: format conversion (DICOM to NIfTI, PNG, HDF5), batch processing, ML dataset preparation, research data export, and imaging ETL workflows. Use when converting DICOM to other formats, preparing imaging datasets for machine learning, building research data pipelines, batch processing medical images, extracting imaging features, or automating imaging workflows. Source: aurabx/skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/aurabx/skills --skill medical imaging pipelines Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/aurabx/skills