{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/gastrovision-a-multi-class-endoscopy-image","title":"GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection","arxiv_id":"2307.08140","date":"2023-07-16","proceeding":null,"authors":["Debesh Jha","Vanshali Sharma","Neethi Dasu","Nikhil Kumar Tomar","Steven Hicks","M. K. Bhuyan","Pradip K. Das","Michael A. Riegler","Pål Halvorsen","Ulas Bagci","Thomas de Lange"],"abstract":"Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges such as scalability and acceptance. These challenges include data availability, biased outcomes, data quality, lack of transparency, and underperformance on unseen datasets from different distributions. The scarcity of large-scale, precisely labeled, and diverse datasets are the major challenge for clinical integration. This scarcity is also due to the legal restrictions and extensive manual efforts required for accurate annotations from clinicians. To address these challenges, we present \\textit{GastroVision}, a multi-center open-access gastrointestinal (GI) endoscopy dataset that includes different anatomical landmarks, pathological abnormalities, polyp removal cases and normal findings (a total of 27 classes) from the GI tract. The dataset comprises 8,000 images acquired from B{\\ae}rum Hospital in Norway and Karolinska University Hospital in Sweden and was annotated and verified by experienced GI endoscopists. Furthermore, we validate the significance of our dataset with extensive benchmarking based on the popular deep learning based baseline models. We believe our dataset can facilitate the development of AI-based algorithms for GI disease detection and classification. Our dataset is available at \\url{https://osf.io/84e7f/}.","url_abs":"https://arxiv.org/abs/2307.08140v2","url_pdf":"https://arxiv.org/pdf/2307.08140v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"gastrovision-a-multi-class-endoscopy-image","repo_url":"https://github.com/debeshjha/gastrovision","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2307.08140","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.08140"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/debeshjha/gastrovision","reach":{"status":"ok"}}],"summary":{"ran":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"c128694a00a1012b","entry":"validate_net","repo":"debeshjha/gastrovision","repo_kind":"official","path":"Source/Validate.py","file_url":"https://github.com/debeshjha/gastrovision/blob/HEAD/Source/Validate.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c128694a00a1012b"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}