{"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/a-large-annotated-medical-image-dataset-for","title":"A large annotated medical image dataset for the development and evaluation of segmentation algorithms","arxiv_id":"1902.09063","date":"2019-02-25","proceeding":null,"authors":["Amber L. Simpson","Michela Antonelli","Spyridon Bakas","Michel Bilello","Keyvan Farahani","Bram van Ginneken","Annette Kopp-Schneider","Bennett A. Landman","Geert Litjens","Bjoern Menze","Olaf Ronneberger","Ronald M. Summers","Patrick Bilic","Patrick F. Christ","Richard K. G. Do","Marc Gollub","Jennifer Golia-Pernicka","Stephan H. Heckers","William R. Jarnagin","Maureen K. McHugo","Sandy Napel","Eugene Vorontsov","Lena Maier-Hein","M. Jorge Cardoso"],"abstract":"Semantic segmentation of medical images aims to associate a pixel with a\nlabel in a medical image without human initialization. The success of semantic\nsegmentation algorithms is contingent on the availability of high-quality\nimaging data with corresponding labels provided by experts. We sought to create\na large collection of annotated medical image datasets of various clinically\nrelevant anatomies available under open source license to facilitate the\ndevelopment of semantic segmentation algorithms. Such a resource would allow:\n1) objective assessment of general-purpose segmentation methods through\ncomprehensive benchmarking and 2) open and free access to medical image data\nfor any researcher interested in the problem domain. Through a\nmulti-institutional effort, we generated a large, curated dataset\nrepresentative of several highly variable segmentation tasks that was used in a\ncrowd-sourced challenge - the Medical Segmentation Decathlon held during the\n2018 Medical Image Computing and Computer Aided Interventions Conference in\nGranada, Spain. Here, we describe these ten labeled image datasets so that\nthese data may be effectively reused by the research community.","url_abs":"http://arxiv.org/abs/1902.09063v1","url_pdf":"http://arxiv.org/pdf/1902.09063v1.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":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/ElliotY-ML/Hippocampus_Segmentation_MRI","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/Rajwrita/Brain-Tumor-Auto-Segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/Soft953/MedicalSegmentationDecathlon","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/alexssanchez/unet-app-pucp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/aws-samples/amazon-sagemaker-spleen-image-segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT-0"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/b4shy/Medical","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/evavanweenen/u-net","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/iyerkrithika21/mesh2ssm_2023","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/korotulea/Quantifying-Hippocampus-Volume-for-Alzheimers-Progression-AI-Assistant","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/tamerthamoqa/3D-mri-brain-tumour-image-segmentation-medical-decathlon-tensorflow","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/wasserth/totalsegmentator","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"a-large-annotated-medical-image-dataset-for","repo_url":"https://github.com/zamnius/uNet-seg-decathlon","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[{"slug":"medical-segmentation-decathlon","name":"Medical Segmentation Decathlon","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1902.09063","atlas_url":"https://app.syntology.ai/?focus=1902.09063","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1902.09063"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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. 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