Nuclei instance segmentation and classification in histopathology images with StarDist

Martin Weigert, Uwe Schmidt
3/3/2022
cs.CV

Official code: stardist/stardist (1,285 stars, BSD-3-Clause, last commit 2026-02-14).

Abstract

Instance segmentation and classification of nuclei is an important task in computational pathology. We show that StarDist, a deep learning nuclei segmentation method originally developed for fluorescence microscopy, can be extended and successfully applied to histopathology images. This is substantiated by conducting experiments on the Lizard dataset, and through entering the Colon Nuclei Identification and Counting (CoNIC) challenge 2022, where our approach achieved the first spot on the leaderboard for the segmentation and classification task for both the preliminary and final test phase.

View on arXivView PDF

Code Implementations(1)

stardist/stardistOfficial100%
BSD-3-Clause

StarDist - Object Detection with Star-convex Shapes

1,285285C, C++Jun 26, 20188 months agoBSD-3-Clause
bioimage-analysiscell-segmentationdeep-learningnuclei-segmentationobject-detection+1 more

Similar Papers

Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification

90% match2023

Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation

90% match1 repo102023

A three in one bottom-up framework for simultaneous semantic segmentation, instance segmentation and classification of multi-organ nuclei in digital cancer histology

90% match2023

Channel Boosted CNN-Transformer-based Multi-Level and Multi-Scale Nuclei Segmentation

89% match2024

Improving Generalization Capability of Deep Learning-Based Nuclei Instance Segmentation by Non-deterministic Train Time and Deterministic Test Time Stain Normalization

89% match2023

HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images

89% match1 repo7462018

Cite this paper

@article{weigert2022nuclei,
  title  = {Nuclei instance segmentation and classification in histopathology images with StarDist},
  author = {Martin Weigert and Uwe Schmidt},
  year   = {2022},
  eprint = {2203.02284},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2203.02284}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2203.02284.svg)](https://codeofpaper.com/paper/2203.02284)

Discussion