mlsanityData to 7 Oct 2026

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

arXiv 2303.06274 ↗First posted 11 Mar 2023cs.CV cs.LGcited by 33

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Abstract (arXiv)

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). Builds on 45 of its 80 references that are in the map. First posted on arXiv 11 Mar 2023.

Builds on

45 of 80 references.

References · 45

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  19. 2021Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classificationcited by 89
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 8; 2025: 12; 2026: 8.

33 papers.

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  1. 2023The Multi-modality Cell Segmentation Challenge: Towards Universal Solutionscited by 39
  2. 2023NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological Imagescited by 29
  3. 2023Domain Generalization in Computational Pathology: Survey and Guidelinescited by 29
  4. 2025A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Modelcited by 12
  5. 2024DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactionscited by 8
  6. 2025PathDiff: Histopathology Image Synthesis with Unpaired Text and Mask Conditionscited by 8
  7. 2024Tissue Concepts: supervised foundation models in computational pathologycited by 7
  8. 2025Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challengescited by 5
  9. 2024CAMP: Continuous and Adaptive Learning Model in Pathologycited by 4
  10. 2024Benchmarking Domain Generalization Algorithms in Computational Pathologycited by 3
  11. 2025RepSNet: A Nucleus Instance Segmentation model based on Boundary Regression and Structural Re-parameterizationcited by 2
  12. 2023An Automated Pipeline for Tumour-Infiltrating Lymphocyte Scoring in Breast Cancercited by 1
21 more
  1. 2024Unlocking adaptive digital pathology through dynamic feature learningcited by 1
  2. 2025A Lightweight and Extensible Cell Segmentation and Classification Model for Whole Slide Imagescited by 1
  3. 2025PhenoBench: A Comprehensive Benchmark for Cell Phenotypingcited by 1
  4. 2025Tissue Aware Nuclei Detection and Classification Model for Histopathology Imagescited by 1
  5. 2023Nuclear Pleomorphism in Canine Cutaneous Mast Cell Tumors: Comparison of Reproducibility and Prognostic Relevance between Estimates, Manual Morphometry and Algorithmic Morphometrycited by 0
  6. 2024A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attentioncited by 0
  7. 2024Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysiscited by 0
  8. 2024Patherea: Cell Detection and Classification for the 2020scited by 0
  9. 2025HistoSmith: Single-Stage Histology Image-Label Generation via Conditional Latent Diffusion for Enhanced Cell Segmentation and Classificationcited by 0
  10. 2025CellVTA: Enhancing Vision Foundation Models for Accurate Cell Segmentation and Classificationcited by 0
  11. 2025A Novel Approach to Linking Histology Images with DNA Methylationcited by 0
  12. 2025A Comparison of Deep Learning Methods for Cell Detection in Digital Cytologycited by 0
  13. 2025Med-2D SegNet: A Light Weight Deep Neural Network for Medical 2D Image Segmentationcited by 0
  14. 2026PanopMamba: Vision State Space Modeling for Nuclei Panoptic Segmentationcited by 0
  15. 2026Learning Class Difficulty via Dynamic Focal Attention for Histopathology Segmentationcited by 0
  16. 2026Dino-NestedUNet: Unlocking Foundation Vision Encoders for Pathology Tumor Bulk Segmentation via Dense Decodingcited by 0
  17. 2026NucEval: A Robust Evaluation Framework for Nuclear Instance Segmentationcited by 0
  18. 2026Deep Reprogramming Distillation for Medical Foundation Modelscited by 0
  19. 2026One Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentationcited by 0
  20. 2026Count Anythingcited by 0
  21. 2026CoM3eT: A foundation model for medical image analysis through federated, multidimensional context integrationcited by 0