mlsanityData to 7 Oct 2026

A multi-centre polyp detection and segmentation dataset for generalisability assessment

arXiv 2106.04463 ↗First posted 8 Jun 2021eess.IV cs.CV cs.LGcited by 63

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Abstract (arXiv)

Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp's number, size and surface structure are linked to the risk of colon cancer. Several methods have been developed to automate polyp detection and segmentation. However, the main issue is that they are not tested rigorously on a large multicentre purpose-built dataset, one reason being the lack of a comprehensive public dataset. As a result, the developed methods may not generalise to different population datasets. To this extent, we have curated a dataset from six unique centres incorporating more than 300 patients. The dataset includes both single frame and sequence data with 3762 annotated polyp labels with precise delineation of polyp boundaries verified by six senior gastroenterologists. To our knowledge, this is the most comprehensive detection and pixel-level segmentation dataset (referred to as textitPolypGen) curated by a team of computational scientists and expert gastroenterologists. The paper provides insight into data construction and annotation strategies, quality assurance, and technical validation. Our dataset can be downloaded from url https://doi.org/10.7303/syn26376615.

Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). Builds on 9 of its 46 references that are in the map. First posted on arXiv 8 Jun 2021.

Builds on

9 of 46 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  4. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  5. 2016Pyramid Scene Parsing Networkcited by 2,472
  6. 2020Adaptive Federated Optimizationcited by 1,036
  7. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 588
  8. 2017Road Extraction by Deep Residual U-Netcited by 333
  9. 2017Optic Disc and Cup Segmentation Methods for Glaucoma Detection with Modification of U-Net Convolutional Neural Networkcited by 16

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 12; 2024: 16; 2025: 19; 2026: 15.

63 papers.

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  1. 2024Foundation Models for Biomedical Image Segmentation: A Surveycited by 28
  2. 2022Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challengecited by 27
  3. 2023TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testingcited by 26
  4. 2025MedSAM3: Delving into Segment Anything with Medical Conceptscited by 25
  5. 2023GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detectioncited by 20
  6. 2024REAL-Colon: A dataset for developing real-world AI applications in colonoscopycited by 20
  7. 2023S2ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentationcited by 15
  8. 2024Frontiers in Intelligent Colonoscopycited by 13
  9. 2025SAM2 for Image and Video Segmentation: A Comprehensive Surveycited by 13
  10. 2025EndoBench: A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysiscited by 13
  11. 2023A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trendscited by 12
  12. 2023Using Diffusion Models to Generate Synthetic Labelled Data for Medical Image Segmentationcited by 10
38 more
  1. 2025Winsor-CAM: Human-Tunable Visual Explanations from Deep Networks via Layer-Wise Winsorizationcited by 10
  2. 2024Polyp SAM 2: Advancing Zero shot Polyp Segmentation in Colorectal Cancer Detectioncited by 8
  3. 2024SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cuescited by 6
  4. 2024Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 Modelcited by 6
  5. 2026MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learningcited by 6
  6. 2024Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Surveycited by 5
  7. 2024DB-SAM: Delving into High Quality Universal Medical Image Segmentationcited by 5
  8. 2023A Client-server Deep Federated Learning for Cross-domain Surgical Image Segmentationcited by 4
  9. 2023Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challengescited by 3
  10. 2023Gall Bladder Cancer Detection from US Images with Only Image Level Labelscited by 3
  11. 2024ECC-PolypDet: Enhanced CenterNet with Contrastive Learning for Automatic Polyp Detectioncited by 3
  12. 2025Robust Polyp Detection and Diagnosis through Compositional Prompt-Guided Diffusion Modelscited by 3
  13. 2025LGPS: A Lightweight GAN-Based Approach for Polyp Segmentation in Colonoscopy Imagescited by 3
  14. 2025PolypSegTrack: Unified Foundation Model for Colonoscopy Video Analysiscited by 3
  15. 2024Harmonized Spatial and Spectral Learning for Robust and Generalized Medical Image Segmentationcited by 2
  16. 2024Leveraging Pre-trained Models for Robust Federated Learning for Kidney Stone Type Recognitioncited by 2
  17. 2025Segment Anything for Video: A Comprehensive Review of Video Object Segmentation and Tracking from Past to Futurecited by 2
  18. 2025Interpretable Similarity of Synthetic Image Utilitycited by 2
  19. 2023TransRUPNet for Improved Polyp Segmentationcited by 1
  20. 2024PolypNextLSTM: A lightweight and fast polyp video segmentation network using ConvNext and ConvLSTMcited by 1
  21. 2024Exploiting Scale-Variant Attention for Segmenting Small Medical Objectscited by 1
  22. 2024Confident magnitude-based neural network pruningcited by 1
  23. 2024FedGS: Federated Gradient Scaling for Heterogeneous Medical Image Segmentationcited by 1
  24. 2025Reducing False Ventricular Tachycardia Alarms in ICU Settings: A Machine Learning Approachcited by 1
  25. 2025RRTS Dataset: A Benchmark Colonoscopy Dataset from Resource-Limited Settings for Computer-Aided Diagnosis Researchcited by 1
  26. 2026Scaling Vision Language Models for Pharmaceutical Long Form Video Reasoning on Industrial GenAI Platformcited by 1
  27. 2026Colon-Bench: An Agentic Workflow for Scalable Dense Lesion Annotation in Full-Procedure Colonoscopy Videoscited by 1
  28. 2026GEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AIcited by 1
  29. 2023Prototype Learning for Out-of-Distribution Polyp Segmentationcited by 0
  30. 2023Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Datacited by 0
  31. 2023Bayesian uncertainty-weighted loss for improved generalisability on polyp segmentation taskcited by 0
  32. 2024Federated Black-Box Adaptation for Semantic Segmentationcited by 0
  33. 2025MGFI-Net: A Multi-Grained Feature Integration Network for Enhanced Medical Image Segmentationcited by 0
  34. 2025The Power of Certainty: How Confident Models Lead to Better Segmentationcited by 0
  35. 2025FreeVPS: Repurposing Training-Free SAM2 for Generalizable Video Polyp Segmentationcited by 0
  36. 2025YOLO-LAN: Precise Polyp Detection via Optimized Loss, Augmentations and Negativescited by 0
  37. 2025PVTAdpNet: Polyp Segmentation using Pyramid vision transformer with a novel Adapter blockcited by 0
  38. 2025Colon-X: Advancing Intelligent Colonoscopy toward Clinical Reasoningcited by 0

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