{"id":"W4405873576","doi":"10.1515/bmt-2024-0396","title":"<i>MedShapeNet</i> – a large-scale dataset of 3D medical shapes for computer vision","year":2024,"lang":"en","type":"article","venue":"Biomedizinische Technik/Biomedical Engineering","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Foothills Medical Centre; École de Technologie Supérieure; University of Calgary; Vector Institute; University of Toronto; University Health Network","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute; Otto von Guericke University Magdeburg; Leibniz-Gemeinschaft; Perelman School of Medicine, University of Pennsylvania; Technische Universität Dortmund; Harokopio University; Universidade do Minho; Università di Pisa; Universitair Medisch Centrum Groningen; RWTH Aachen University; National and Kapodistrian University of Athens; Medizinischen Hochschule Hannover; Université de Bourgogne; Deutsches Krebsforschungszentrum; Centre National de la Recherche Scientifique; University of Pennsylvania; Universiteit Gent; Deutschen Konsortium für Translationale Krebsforschung; Vrije Universiteit Brussel; Nvidia; Radboud Universitair Medisch Centrum; KU Leuven; Radboud Universiteit; Austrian Science Fund; Universität Duisburg-Essen; Stryker; National Natural Science Foundation of China; European Regional Development Fund; Bundesministerium für Bildung und Forschung; Technische Universität Braunschweig; Universitätsklinikum Essen; University of Bern; Rijksuniversiteit Groningen; Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen; TU Graz, Internationale Beziehungen und Mobilitätsprogramme","keywords":"Scale (ratio); Artificial intelligence; Computer science; Computer vision; Computer graphics (images); Pattern recognition (psychology); Cartography; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00133336,0.0004509277,0.0007159919,0.0007697426,0.00005867259,0.00008090871,0.0007230025,0.0005149147,0.0004590611],"category_scores_gemma":[0.0002073779,0.0003816333,0.0002608862,0.00128838,0.0002643563,0.0002107151,0.0002334314,0.0006173374,0.00007139854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005434191,"about_ca_system_score_gemma":0.00009391937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005822672,"about_ca_topic_score_gemma":0.000001389638,"domain_scores_codex":[0.9963046,0.0000203593,0.001013635,0.0005872056,0.001248109,0.0008261157],"domain_scores_gemma":[0.9982527,0.0004908768,0.00004780058,0.0004100369,0.00005242059,0.000746203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002296923,0.0005486569,0.00002025195,0.008657724,0.00109715,0.0004032826,0.0003736815,0.001687283,0.1374435,0.001047027,0.4438559,0.4048426],"study_design_scores_gemma":[0.0003358607,0.00007588008,0.000009856706,0.0006067686,0.00007823486,0.00003990403,0.00001148799,0.5613149,0.001047497,0.00001371282,0.4362074,0.0002585638],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002198068,0.002936173,0.9878688,0.0008459716,0.001553505,0.0003235214,0.001806665,0.002325057,0.0001421747],"genre_scores_gemma":[0.6007925,0.001398316,0.3818438,0.000816122,0.005320857,0.0005284296,0.008580778,0.0005861286,0.0001330449],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.606025,"threshold_uncertainty_score":0.9998636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006521123734136209,"score_gpt":0.2577179367065606,"score_spread":0.2511968129724244,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}