{"id":"W4380148842","doi":"10.1016/j.media.2023.102863","title":"A survey on deep learning for skin lesion segmentation","year":2023,"lang":"en","type":"review","venue":"Medical Image Analysis","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":178,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Google; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Institutes of Health Research; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação para a Ciência e a Tecnologia; Fundação de Amparo à Pesquisa do Estado de São Paulo; BC Cancer Foundation; National Science Foundation","keywords":"Artificial intelligence; Segmentation; Deep learning; Skin lesion; Computer vision; Computer science; Pattern recognition (psychology); Lesion; Medicine; Dermatology; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008953179,0.00116134,0.001513288,0.002699455,0.0002057361,0.001215279,0.00112638,0.001171132,0.004710458],"category_scores_gemma":[0.002414641,0.0004645858,0.001310955,0.003335122,0.0003723179,0.001355952,0.0008329092,0.001282478,0.001984745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004882444,"about_ca_system_score_gemma":0.001552648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003631347,"about_ca_topic_score_gemma":0.005005791,"domain_scores_codex":[0.999708,0.00005274967,0.00004884282,0.00007643623,0.00009105429,0.0000228829],"domain_scores_gemma":[0.9989856,0.0006777324,0.00007417042,0.00003369134,0.0001929672,0.00003584138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004350066,0.0000577218,0.0003334374,0.01065109,0.0001723667,0.00004741626,0.00001846116,0.001154162,0.0006783195,0.001031955,0.01686328,0.9689483],"study_design_scores_gemma":[0.00009134242,0.0005673997,0.004665862,0.01982801,0.001910107,0.001876777,0.00011924,0.01152743,0.005728536,0.01021407,0.9433198,0.0001515102],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004186807,0.9941041,0.003579214,0.0003381236,0.0002188659,0.00001373233,0.0001305815,0.00005778253,0.001138942],"genre_scores_gemma":[0.00301002,0.9909243,0.003711938,0.000456414,0.0004103829,0.00001801838,0.0003200936,0.00002722265,0.001121604],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004710458,"threshold_uncertainty_score":0.0157581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07588093704665991,"score_gpt":0.4023016891922042,"score_spread":0.3264207521455443,"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."}}