mlsanityData to 7 Oct 2026

CoNIC: Colon Nuclei Identification and Counting Challenge 2022

arXiv 2111.14485 ↗First posted 29 Nov 2021cs.CVcited by 44

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Abstract (arXiv)

Nuclear segmentation, classification and quantification within Haematoxylin & Eosin stained histology images enables the extraction of interpretable cell-based features that can be used in downstream explainable models in computational pathology (CPath). However, automatic recognition of different nuclei is faced with a major challenge in that there are several different types of nuclei, some of them exhibiting large intra-class variability. To help drive forward research and innovation for automatic nuclei recognition in CPath, we organise the Colon Nuclei Identification and Counting (CoNIC) Challenge. The challenge encourages researchers to develop algorithms that perform segmentation, classification and counting of nuclei within the current largest known publicly available nuclei-level dataset in CPath, containing around half a million labelled nuclei. Therefore, the CoNIC challenge utilises over 10 times the number of nuclei as the previous largest challenge dataset for nuclei recognition. It is important for algorithms to be robust to input variation if we wish to deploy them in a clinical setting. Therefore, as part of this challenge we will also test the sensitivity of each submitted algorithm to certain input variations.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). Builds on 11 of its 16 references that are in the map. First posted on arXiv 29 Nov 2021.

Builds on

11 of 16 references.

References · 11

  1. 2018Panoptic Segmentationcited by 796
  2. 2018Explaining Explanations: An Overview of Interpretability of Machine Learningcited by 508
  3. 2018HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Imagescited by 387
  4. 2016Gland Segmentation in Colon Histology Images: The GlaS Challenge Contestcited by 203
  5. 2020PanNuke Dataset Extension, Insights and Baselinescited by 113
  6. 2021Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classificationcited by 89
  7. 2018MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Imagescited by 87
  8. 2020Quantifying Explainers of Graph Neural Networks in Computational Pathologycited by 35
  9. 2017Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathologycited by 13
  10. 2021ALBRT: Cellular Composition Prediction in Routine Histology Imagescited by 8
  11. 2021Now You See It, Now You Dont: Adversarial Vulnerabilities in Computational Pathologycited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 16; 2023: 13; 2024: 8; 2025: 4; 2026: 3.

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  1. 2023CellViT: Vision Transformers for Precise Cell Segmentation and Classificationcited by 108
  2. 2022One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classificationcited by 38
  3. 2023CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Countingcited by 33
  4. 2022Nuclei instance segmentation and classification in histopathology images with StarDistcited by 31
  5. 2024Interactive Medical Image Segmentation: A Benchmark Dataset and Baselinecited by 30
  6. 2023Domain Generalization in Computational Pathology: Survey and Guidelinescited by 29
  7. 2023Rethinking Boundary Detection in Deep Learning Models for Medical Image Segmentationcited by 9
  8. 2024BoNuS: Boundary Mining for Nuclei Segmentation with Partial Point Labelscited by 8
  9. 2022SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular Layoutscited by 6
  10. 2023Interpretable histopathology-based prediction of disease relevant features in Inflammatory Bowel Disease biopsies using weakly-supervised deep learningcited by 6
  11. 2023Nucleus-aware Self-supervised Pretraining Using Unpaired Image-to-image Translation for Histopathology Imagescited by 6
  12. 2024StainFuser: Controlling Diffusion for Faster Neural Style Transfer in Multi-Gigapixel Histology Imagescited by 6
32 more
  1. 2022Panoptic segmentation with highly imbalanced semantic labelscited by 5
  2. 2022Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future Directionscited by 5
  3. 2023Nuclear Segmentation and Classification: On Color & Compression Generalizationcited by 4
  4. 2024CAMP: Continuous and Adaptive Learning Model in Pathologycited by 4
  5. 2022ConvNeXt-backbone HoVerNet for nuclei segmentation and classificationcited by 3
  6. 2022Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Countingcited by 3
  7. 2024Few-Shot Learning for Annotation-Efficient Nucleus Instance Segmentationcited by 3
  8. 2022ciscNet -- A Single-Branch Cell Instance Segmentation and Classification Networkcited by 2
  9. 2023Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learningcited by 2
  10. 2025RepSNet: A Nucleus Instance Segmentation model based on Boundary Regression and Structural Re-parameterizationcited by 2
  11. 2022Using Multi-scale SwinTransformer-HTC with Data augmentation in CoNIC Challengecited by 1
  12. 2022Colon Nuclei Instance Segmentation using a Probabilistic Two-Stage Detectorcited by 1
  13. 2022Color Space-based HoVer-Net for Nuclei Instance Segmentation and Classificationcited by 1
  14. 2022MGTUNet: An new UNet for colon nuclei instance segmentation and quantificationcited by 1
  15. 2023More From Less: Self-Supervised Knowledge Distillation for Routine Histopathology Datacited by 1
  16. 2023Semi-supervised Cell Recognition under Point Supervisioncited by 1
  17. 2023Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signaturescited by 1
  18. 2023Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classificationcited by 1
  19. 2024Nucleus subtype classification using inter-modality learningcited by 1
  20. 2022A Standardized Pipeline for Colon Nuclei Identification and Counting Challengecited by 0
  21. 2022Separable-HoverNet and Instance-YOLO for Colon Nuclei Identification and Countingcited by 0
  22. 2022MF-Hovernet: An Extension of Hovernet for Colon Nuclei Identification and Counting (CoNiC) Challengecited by 0
  23. 2022Cellular Segmentation and Composition in Routine Histology Images using Deep Learningcited by 0
  24. 2023Stain Consistency Learning: Handling Stain Variation for Automatic Digital Pathology Segmentationcited by 0
  25. 2024Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathologycited by 0
  26. 2024CellPilot: A unified approach to automatic and interactive segmentation in histopathologycited by 0
  27. 2025Optimal Transport Driven Asymmetric Image-to-Image Translation for Nuclei Segmentation of Histological Imagescited by 0
  28. 2025Image-Based Method For Measuring And Classification Of Iron Ore Pellets Using Star-Convex Polygonscited by 0
  29. 2025Cancer cytoplasm segmentation in hyperspectral cell image with data augmentationcited by 0
  30. 2026SGDC: Structurally-Guided Dynamic Convolution for Medical Image Segmentationcited by 0
  31. 2026Maximum Matching Accuracy: An Instance Segmentation Evaluation Metric Utilizing Globally Optimal Matchingcited by 0
  32. 2026HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopycited by 0