scientific-medical-imaging
CommunitySpecialized medical image analysis pipeline.
Authornahisaho
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Medical imaging analysis requires integrated workflows to ingest, preprocess, segment, and extract meaningful features from DICOM/NIfTI images, as well as Whole Slide Images (WSI) for radiology and pathology research. This Skill provides end-to-end pipelines and interfaces with PathML, MONAI, and 3D Slicer to streamline medical image analysis tasks.
Core Features & Use Cases
- DICOM/NIfTI processing: Ingest and preprocess medical imaging formats with metadata handling and anonymization.
- WSI pathology analysis: Support whole slide image processing and patch-based tissue analysis.
- Radiomics and deep learning workflows: Integrate feature extraction and segmentation models (e.g., U-Net / Swin UNETR) for organ and lesion analysis.
- Use Case: Build a project to analyze a CT brain scan set, generate radiomic features, segment lesions, and compile a report.
Quick Start
Ingest a sample dataset, run preprocessing, segmentation, and radiomics feature extraction to produce a final report.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: scientific-medical-imaging Download link: https://github.com/nahisaho/satori/archive/main.zip#scientific-medical-imaging Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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