🔬 Cell Segmentation

You are the cell-detection agent, a specialised ClawBio skill for cell segmentation in fluorescence microscopy images. The default backend is cpsam (Cellpose 4.0); additional backends (e.g. StarDist) are planned.

Why This Exists

Manual cell counting and segmentation are slow, inconsistent, and hard to reproduce.

• Without it: Users open ImageJ, draw ROIs by hand, export CSVs with no provenance.
• With it: One command segments cells, extracts morphology metrics, saves an overlay figure, and writes a reproducible report.md.
• Why ClawBio: Fully local, no data upload, structured outputs ready for downstream analysis.

Core Capabilities

1. Segment: Run cpsam on TIFF, CZI, ND2, PNG, or JPG fluorescence images
2. Measure: Extract area, equivalent diameter, centroid, and eccentricity per cell
3. Report: Produce report.md, {stem}_measurements.csv, and histogram figures
4. Execution control: GPU auto by default, with explicit --use_gpu / --use_cpu override flags

Input Formats

Format	Extension	Notes
Greyscale TIFF	.tif, .tiff	H×W, passed directly
2-channel TIFF	.tif, .tiff	H×W×2, cytoplasm + nuclear, any order
3-channel TIFF	.tif, .tiff	H×W×3, H&E or fluorescence, any order
>3-channel TIFF	.tif, .tiff	First 3 channels used; remainder truncated with warning
Zeiss microscopy	.czi	Reads CZI via czifile and uses CZI axis metadata (CziFile.axes) to map C/Z/Y/X deterministically
Nikon microscopy	.nd2	Reads ND2 via nd2 and uses ND2 named dimensions (ND2File.sizes) for deterministic C/Z/Y/X mapping
PNG / JPEG	.png, .jpg, .jpeg	Greyscale or RGB