Usage

Step 1 — Create ROI (QuPath)

1. Open your .vsi slide in QuPath
2. Navigate to the region of interest
3. Run MyoPath1_roi.groovy in QuPath Script Editor (Automate → Show script editor)
4. A 1500 µm × 1500 µm square ROI appears centered on your view

TIP

The ROI size is standardized to ensure consistent tissue sampling across slides.

Step 2 — Segment Tissues (QuPath)

1. Select the ROI created in Step 1 (click on it)
2. Run MyoPath2_segment.groovy
3. Wait for three-layer segmentation to complete:
   • Muscle fibers via Cellpose-SAM (~30–60 s with GPU)
   • Fat regions via pixel classifier (~5 s)
   • Nuclei via watershed (~10 s)
4. All annotations appear as independent objects with color coding:

Color	Tissue
Red	Muscle Fiber
Yellow	Fat
Blue	Nucleus

Key Parameters

The script exposes several parameters that can be tuned for your tissue:

Muscle fiber segmentation (muscleFiberParams):

Parameter	Default	Description
expectedDiameterMicrons	80	Expected myofiber diameter in µm. If fibers are consistently missed or over-merged, adjust this to match the typical fiber caliber in your samples
downsample	10.0	Controls segmentation resolution. Lower values give finer detail but increase memory usage and processing time; higher values are faster but coarser

Fat detection (fatParams):

Parameter	Default	Description
splitThreshold	0.1	Threshold for splitting fat regions from the pixel classifier. The default works with the provided Fat in muscle classifier; if you train your own classifier in QuPath, you may need to adjust this value

Nucleus detection (nucleusParams):

Parameter	Default	Description
threshold	—	Detection threshold on the Hematoxylin channel signal intensity. Increase to detect fewer (higher-confidence) nuclei; decrease to detect more (at the risk of false positives). Optimal value depends on staining intensity

WARNING

The fourth tissue layer — connective tissue — is computed by Boolean subtraction in Step 4, not annotated directly in QuPath.

Step 3 — Export Data (QuPath)

1. Select the ROI again
2. Run MyoPath3_export.groovy
3. Output saved to exports/{image_name}/:

exports/HE_M3669/
├── HE_M3669_ROI.tiff             # Full-resolution ROI image
├── HE_M3669_ROI.jpg              # JPEG preview
├── HE_M3669_annotations.geojson  # All annotations
└── HE_M3669_summary.txt          # Export summary

Step 4 — Batch Analysis (Python)

cd MyoPath

# Test with a single sample
python MyoPath4_analysis.py --test HE_M3669

# Process all samples
python MyoPath4_analysis.py --all --cores 16

# Process specific samples
python MyoPath4_analysis.py --samples HE_M1600,HE_M2806

# Custom input/output directories
python MyoPath4_analysis.py --all --input /data/exports --output /data/results

# Debug mode (single process)
python MyoPath4_analysis.py --test HE_M3669 --sequential --verbose

CLI Options

Flag	Default	Description
--test NAME	—	Test a single sample
--samples A,B	—	Process specific samples (comma-separated)
--all	—	Process all samples in exports/
--input DIR	../exports	Exports directory path
--output DIR	../results	Results directory path
--cores N	10	CPU cores for parallel processing
--sequential	off	Single-process mode (for debugging)
--verbose	off	Detailed logging

Output Structure

Each processed sample produces per-sample results in the exports directory, plus aggregated results:

exports/{sample_name}/                    # Per-sample results
├── {sample}_statistics.json             # Tissue area statistics
├── {sample}_dystrophy_report.json       # Full pathology report
├── original_image.png                   # H&E image
├── standard_segmentation.png            # 4-tissue overlay
├── muscle_fiber_colormap.png            # Individual fiber colors
└── three_view_comparison.png            # Side-by-side comparison

results/                                  # Aggregated results
└── batch_analysis_summary.json          # Batch processing summary

Visualization Outputs

File	Description
original_image.png	Raw H&E-stained tissue image
standard_segmentation.png	Color-coded overlay of all four tissue types
muscle_fiber_colormap.png	Each myofiber rendered in a unique color for instance-level inspection
three_view_comparison.png	Side-by-side panel: original, segmentation, and fiber colormap

Dystrophy Report

The JSON report (*_dystrophy_report.json) includes all 7 pathology indicators and an overall MyoPath Score (0–100):

Score Range	Severity
0–20	Normal / Minimal
20–40	Mild
40–60	Moderate
60–100	Severe

See Morphometric Features for detailed definitions of each indicator and their clinical interpretation.