Irregular cell shape segmentation using VollSeg

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VollSeg is more than just a single segmentation algorithm; it is a meticulously designed modular segmentation tool tailored to diverse model organisms and imaging methods. While a U-Net might suffice for certain image samples, others might benefit from utilizing StarDist, and some could require a blend of both, potentially coupled with denoising or region of interest models. The pivotal decision left to make is how to select the most appropriate VollSeg configuration for your dataset, a question we comprehensively address in our documentation website.

This project provides the napari plugin for VollSeg, a deep learning based 2D and 3D segmentation tool for irregular shaped cells. VollSeg has originally been developed (see papers) for the segmentation of densely packed membrane labelled cells in challenging images with low signal-to-noise ratios. The plugin allows to apply pretrained and custom trained models from within napari. For detailed demo of the plugin see these videos and a short video about the parameter selection


  • 2.4.7

Last updated:

  • 03 September 2023

First released:

  • 10 December 2021


Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 12
  • Forks: 1
  • Issues + PRs: 0

Python versions supported:

Operating system:


  • vollseg
  • napari >=0.4.13
  • magicgui >=0.4.0
  • pyqt6
  • pynvml
  • tensorflow ; platform_system != "Darwin" or platform_machine != "arm64"
  • tensorflow-macos ; platform_system == "Darwin" and platform_machine == "arm64"