mlsanityData to 7 Oct 2026

NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological Images

arXiv 2308.01760 ↗First posted 3 Aug 2023eess.IV cs.CVcited by 29

Not on the map. Why?

Abstract (arXiv)

In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for this task, supervised deep learning (DL) methods have shown superior segmentation performances compared to classical machine learning and image processing techniques. However, these models need fully annotated datasets for training which is challenging to acquire, especially in the medical domain. In this work, we release one of the biggest fully manually annotated datasets of nuclei in Hematoxylin and Eosin (H&E)-stained histological images, called NuInsSeg. This dataset contains 665 image patches with more than 30,000 manually segmented nuclei from 31 human and mouse organs. Moreover, for the first time, we provide additional ambiguous area masks for the entire dataset. These vague areas represent the parts of the images where precise and deterministic manual annotations are impossible, even for human experts. The dataset and detailed step-by-step instructions to generate related segmentation masks are publicly available at https://www.kaggle.com/datasets/ipateam/nuinsseg and https://github.com/masih4/NuInsSeg, respectively.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 18 of its 43 references that are in the map. First posted on arXiv 3 Aug 2023.

Builds on

18 of 43 references.

References · 18

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2017Mask R-CNNcited by 7,259
  4. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,420
  5. 2018Panoptic Segmentationcited by 796
  6. 2018HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Imagescited by 387
  7. 2021Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classificationcited by 89
  8. 2018Methods for Segmentation and Classification of Digital Microscopy Tissue Imagescited by 72
  9. 2017Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Trainingcited by 57
  10. 2021CryoNuSeg: A Dataset for Nuclei Instance Segmentation of Cryosectioned H&E-Stained Histological Imagescited by 50
  11. 2020NuClick: A Deep Learning Framework for Interactive Segmentation of Microscopy Imagescited by 46
  12. 2023CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Countingcited by 33
6 more
  1. 2023OCELOT: Overlapped Cell on Tissue Dataset for Histopathologycited by 29
  2. 2022FUSeg: The Foot Ulcer Segmentation Challengecited by 21
  3. 2020Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Typescited by 16
  4. 2022Nuclei Segmentation with Point Annotations from Pathology Images via Self-Supervised Learning and Co-Trainingcited by 16
  5. 2020Pollen Grain Microscopic Image Classification Using an Ensemble of Fine-Tuned Deep Convolutional Neural Networkscited by 4
  6. 2023A Laplacian Pyramid Based Generative H&E Stain Augmentation Networkcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 7; 2025: 8; 2026: 12.

29 papers.

Sort:

By area:

  1. 2023Domain Generalization in Computational Pathology: Survey and Guidelinescited by 29
  2. 2024InstanSeg: an embedding-based instance segmentation algorithm optimized for accurate, efficient and portable cell segmentationcited by 9
  3. 2025Segment Anything for Histopathologycited by 9
  4. 2024SEINE: Structure Encoding and Interaction Network for Nuclei Instance Segmentationcited by 6
  5. 2024Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantificationcited by 4
  6. 2025A Multi-Stage Auto-Context Deep Learning Framework for Tissue and Nuclei Segmentation and Classification in H&E-Stained Histological Images of Advanced Melanomacited by 4
  7. 2024Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Datacited by 2
  8. 2026Revisiting foundation models for cell instance segmentationcited by 2
  9. 2024Unlocking adaptive digital pathology through dynamic feature learningcited by 1
  10. 2025CellStyle: Improved Zero-Shot Cell Segmentation via Style Transfercited by 1
  11. 2025Unpaired Image-to-Image Translation for Segmentation and Signal Unmixingcited by 1
  12. 2026NucFuseRank: Dataset Fusion and Performance Ranking for Nuclei Instance Segmentationcited by 1
17 more
  1. 2026Towards High-Quality Image Segmentation: Improving Topology Accuracy by Penalizing Neighbor Pixelscited by 1
  2. 2026Measuring Prediction Uncertainty in Neural Cellular Automatacited by 1
  3. 2023Improving Generalization Capability of Deep Learning-Based Nuclei Instance Segmentation by Non-deterministic Train Time and Deterministic Test Time Stain Normalizationcited by 0
  4. 2024NOISe: Nuclei-Aware Osteoclast Instance Segmentation for Mouse-to-Human Domain Transfercited by 0
  5. 2024Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysiscited by 0
  6. 2025Spatial Lifting for Dense Predictioncited by 0
  7. 2025No Masks Needed: Explainable AI for Deriving Segmentation from Classificationcited by 0
  8. 2025Rank-Aware Agglomeration of Foundation Models for Immunohistochemistry Image Cell Countingcited by 0
  9. 2025CellGenNet: A Knowledge-Distilled Framework for Robust Cell Segmentation in Cancer Tissuescited by 0
  10. 2026PanopMamba: Vision State Space Modeling for Nuclei Panoptic Segmentationcited by 0
  11. 2026Is SAM3 ready for pathology segmentation?cited by 0
  12. 2026NucEval: A Robust Evaluation Framework for Nuclear Instance Segmentationcited by 0
  13. 2026Count Anythingcited by 0
  14. 2026HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopycited by 0
  15. 2026A Multimodal Dataset for Survival Prediction in Resected Pancreatic Ductal Adenocarcinomacited by 0
  16. 2026BIABench: Evaluating AI agents on real-world bioimage analysis taskscited by 0
  17. 2026Spatial Lifting for Dense Predictioncited by 0