| name | medical-image-case-report |
| description | Generate research-oriented HTML or Markdown case reports for volumetric
medical images, including summary statistics and slice montages.
|
| version | 1.0.0 |
| author | Medical AI Skills Team |
| license | MIT |
| tags | ["reporting","visualization","nifti","case-report"] |
| maturity | experimental |
| category | reporting |
| requires_extras | ["core","reporting"] |
Medical Image Case Report
Overview
This skill generates a research-facing case report from a volumetric medical image and, optionally, a segmentation mask. It summarizes image dimensions, spacing, intensity statistics, and slice visualizations.
Installation
pip install .[reporting]
Dependencies:
- Python >= 3.10
- nibabel
- numpy
- matplotlib
- Jinja2
- Pillow
Usage
python scripts/main.py IMAGE_PATH [OPTIONS]
Arguments
| Argument | Required | Description |
|---|
IMAGE_PATH | Yes | Path to an input medical image file |
Options
| Option | Default | Description |
|---|
--mask | none | Optional segmentation mask path |
--output | report.html | Output report file |
--format | html | Output format: html or md |
--slices | 5 | Number of montage slices |
--verbose | false | Enable verbose logging |
--version | - | Show version and exit |
--help | - | Show help and exit |
Input Schema
Input is a single medical image file readable by the implementation and an optional mask file aligned to the image grid.
Output Schema
{
"success": true,
"result": {
"report_path": "report.html",
"summary_path": "report.json",
"format": "html",
"has_mask": true
},
"metadata": {
"timestamp": "2024-01-15T10:30:00Z",
"duration_ms": 1234,
"version": "1.0.0"
}
}
Exit Codes
| Code | Meaning |
|---|
| 0 | Success |
| 1 | Validation error |
| 2 | Runtime error |
| 3 | Usage error |
Examples
python scripts/main.py patient_001.nii.gz --output case_report.html
python scripts/main.py scan.nii.gz --mask lesion_mask.nii.gz --format md
References
Disclaimer
For research use only. This skill is not intended for clinical use.
