napari-cilia-segmentation 0.1.2

Napari plugin for ARL13B cilia segmentation in retinal organoids

Cilia Segmentation — napari plugin

Segments ARL13B (647 nm) cilia from retinal organoid OME-TIFF files. Matches Arivis "Long Side, 3D Oriented Bounds" length measurement.

Install

cd cilia_seg_plugin
pip install -e .

Use

1. Open napari
2. Load your OME-TIFF file (File → Open)
3. Go to Plugins → Cilia Segmentation
4. Set your parameters in the panel (voxel sizes, threshold, filters)
5. Press ▶ Run Segmentation
6. Press 💾 Save Results to write CSV + TIFs + panels

Parameters

Parameter	Default	Notes
Cilia channel	1	0=ARR3_488, 1=ARL13B_647, 2=DAPI
VX / VY (µm)	0.0986	Lateral pixel size from Arivis
VZ (µm)	0.240	Axial step size from Arivis
Threshold %	99.7	↑ raise if noisy, ↓ lower if missing cilia
Gaussian sigma	1.0	Smoothing before threshold
Opening radius	1	Morphological opening, 0 to disable
Min voxels	150	Lower for small cilia or large pixels
Exclude border	True	Remove objects touching volume edge
Min length µm	0.992	Matches Arivis lower bound
Max length µm	4.865	Matches Arivis upper bound
Scale bar µm	20	For saved panel images

Outputs (saved to Save directory)

File	Contents
*_YYYYMMDD_HHMMSS.csv	Per-cilium: length, volume, intensity, centroid
*_labels.tif	Integer label map (3D)
*_mask.tif	Binary mask (3D)
*_panel_raw.tif	ARL13B (red) + DAPI (blue), best Z
*_panel_seg.tif	Colour overlay on dimmed grey background
*_panel_merged.tif	Raw + overlay combined

Tuning guide

• Too much noise → raise Threshold % (e.g. 99.8, 99.9)
• Missing cilia → lower Threshold % (e.g. 99.5, 99.3)
• Small blobs remain → raise Min voxels (e.g. 300, 500)
• Missing small cilia → lower Min voxels (e.g. 80, 50)