Endoscopy disease detection challenge 2020
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Abstract (arXiv)
Whilst many technologies are built around endoscopy, there is a need to have a comprehensive dataset collected from multiple centers to address the generalization issues with most deep learning frameworks. What could be more important than disease detection and localization? Through our extensive network of clinical and computational experts, we have collected, curated and annotated gastrointestinal endoscopy video frames. We have released this dataset and have launched disease detection and segmentation challenge EDD2020 https://edd2020.grand-challenge.org to address the limitations and explore new directions. EDD2020 is a crowd sourcing initiative to test the feasibility of recent deep learning methods and to promote research for building robust technologies. In this paper, we provide an overview of the EDD2020 dataset, challenge tasks, evaluation strategies and a short summary of results on test data. A detailed paper will be drafted after the challenge workshop with more detailed analysis of the results.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Mar 2020.
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Citing papers per year: 2022: 3; 2023: 4; 2024: 3; 2025: 3.
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- 2024GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AIcited by 96
- 2022Video Polyp Segmentation: A Deep Learning Perspectivecited by 81
- 2023SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million maskscited by 54
- 2022Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challengecited by 27
- 2023Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospectscited by 22
- 2023GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detectioncited by 20
- 2023Rethinking Exemplars for Continual Semantic Segmentation in Endoscopy Scenes: Entropy-based Mini-Batch Pseudo-Replaycited by 20
- 2024Frontiers in Intelligent Colonoscopycited by 13
- 2025EndoBench: A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysiscited by 13
- 2022Knowledge distillation with a class-aware loss for endoscopic disease detectioncited by 1
- 2024A Medical Data-Effective Learning Benchmark for Highly Efficient Pre-training of Foundation Modelscited by 1
- 2025EndoARSS: Adapting Spatially-Aware Foundation Model for Efficient Activity Recognition and Semantic Segmentation in Endoscopic Surgerycited by 1
1 more
- 2025Colon-X: Advancing Intelligent Colonoscopy toward Clinical Reasoning3 Dec 2025
- 2025EndoARSS: Adapting Spatially-Aware Foundation Model for Efficient Activity Recognition and Semantic Segmentation in Endoscopic Surgery7 Jun 2025
- 2025EndoBench: A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysis29 May 2025
- 2024Frontiers in Intelligent Colonoscopy22 Oct 2024
- 2024GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI6 Aug 2024
- 2024A Medical Data-Effective Learning Benchmark for Highly Efficient Pre-training of Foundation Models31 Jan 2024
- 2023Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospects28 Dec 2023
- 2023SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks20 Nov 2023
- 2023Rethinking Exemplars for Continual Semantic Segmentation in Endoscopy Scenes: Entropy-based Mini-Batch Pseudo-Replay27 Aug 2023
- 2023GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection16 Jul 2023
- 2022Knowledge distillation with a class-aware loss for endoscopic disease detection19 Jul 2022
- 2022Video Polyp Segmentation: A Deep Learning Perspective27 Mar 2022
- 2022Video Polyp Segmentation: A Deep Learning Perspectivecited by 81
- 2023SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million maskscited by 54
- 2022Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challengecited by 27
- 2023Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospectscited by 22
- 2023GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detectioncited by 20
- 2023Rethinking Exemplars for Continual Semantic Segmentation in Endoscopy Scenes: Entropy-based Mini-Batch Pseudo-Replaycited by 20
- 2024Frontiers in Intelligent Colonoscopycited by 13
- 2022Knowledge distillation with a class-aware loss for endoscopic disease detectioncited by 1
- 2024A Medical Data-Effective Learning Benchmark for Highly Efficient Pre-training of Foundation Modelscited by 1
- 2025EndoARSS: Adapting Spatially-Aware Foundation Model for Efficient Activity Recognition and Semantic Segmentation in Endoscopic Surgerycited by 1
- 2025EndoARSS: Adapting Spatially-Aware Foundation Model for Efficient Activity Recognition and Semantic Segmentation in Endoscopic Surgery7 Jun 2025
- 2024Frontiers in Intelligent Colonoscopy22 Oct 2024
- 2024A Medical Data-Effective Learning Benchmark for Highly Efficient Pre-training of Foundation Models31 Jan 2024
- 2023Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospects28 Dec 2023
- 2023SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks20 Nov 2023
- 2023Rethinking Exemplars for Continual Semantic Segmentation in Endoscopy Scenes: Entropy-based Mini-Batch Pseudo-Replay27 Aug 2023
- 2023GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection16 Jul 2023
- 2022Knowledge distillation with a class-aware loss for endoscopic disease detection19 Jul 2022
- 2022Video Polyp Segmentation: A Deep Learning Perspective27 Mar 2022
- 2022Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge24 Feb 2022