> ## Documentation Index
> Fetch the complete documentation index at: https://docs.biom.science/llms.txt
> Use this file to discover all available pages before exploring further.

# Cellpose — Cell Segmentation

> GPU-accelerated cell and nuclei segmentation.

# Cellpose

Cellpose is a deep learning model for cell segmentation. It detects and outlines individual cells in microscopy images, supporting multiple cell types and automatic diameter estimation.

## Input formats

`.png`, `.jpg`, `.jpeg`, `.tiff`, `.bmp`, `.webp`

## Model variants

| Variant             | Description                                            |
| ------------------- | ------------------------------------------------------ |
| **cyto3** (default) | Latest cytoplasm model — best general-purpose accuracy |
| **cyto2**           | Second-generation cytoplasm model                      |
| **cyto**            | Original cytoplasm model                               |
| **nuclei**          | Nuclei-only detection                                  |

## Parameters

| Parameter                      | Range                   | Default  | Description                                          |
| ------------------------------ | ----------------------- | -------- | ---------------------------------------------------- |
| **Model type**                 | cyto/cyto2/cyto3/nuclei | cyto3    | Which Cellpose model to use                          |
| **Diameter**                   | 0–500 px                | 0 (auto) | Expected cell diameter. Set to 0 for auto-detection. |
| **Flow threshold**             | 0–1                     | 0.4      | Maximum flow error per mask (advanced)               |
| **Cell probability threshold** | -6 to +6                | 0.0      | Cell probability cutoff (advanced)                   |
| **Channels**                   | \[int, int]             | \[0, 0]  | Cytoplasm and nucleus channel indices (advanced)     |

## Outputs

| Output            | Format         | Description                           |
| ----------------- | -------------- | ------------------------------------- |
| Segmentation mask | PNG            | Combined instance segmentation mask   |
| Polygons          | JSON (GeoJSON) | Vector outlines of each detected cell |

## Presets

| Preset                | Description                        |
| --------------------- | ---------------------------------- |
| **Cell Segmentation** | cyto3 model with auto-diameter     |
| **Nuclei Only**       | nuclei model for nuclear detection |

## Compute requirements

| Resource | Requirement                                 |
| -------- | ------------------------------------------- |
| GPU      | Required — min 8 GB VRAM, 16 GB recommended |
| Duration | \~30 seconds per image                      |