A napari plugin performing joint denoising and segmentation
of microscopy images using DenoiSeg.

View the Project on GitHub juglab/napari-denoiseg


napari-denoiseg brings DenoiSeg to the fantastic world of napari. DenoiSeg is an algorithm allowing the joint denoising and segmentation of microscopy data using little ground-truth annotation. DenoiSeg is an offshoot of Noise2Void.

This set of plugins can train, retrain and predict on images from napari or from the disk. It conveniently allows saving the models for later use and is compatible with


  1. Installation
  2. Documentation
  3. Examples
  4. Troubleshooting

Report issues and errors

Help us improve the plugin by submitting issues to the Github repository or tagging @jdeschamps on

Cite us

Tim-Oliver Buchholz, Mangal Prakash, Alexander Krull and Florian Jug, “DenoiSeg: Joint Denoising and Segmentationarxiv (2020)


This plugin was developed thanks to the support of the Silicon Valley Community Foundation (SCVF) and the Chan-Zuckerberg Initiative (CZI) with the napari Plugin Accelerator grant 2021-239867.

Distributed under the terms of the BSD-3 license, “napari-denoiseg” is a free and open source software.