{"id":"W2803959545","doi":"10.1016/j.neuroimage.2018.09.081","title":"Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks","year":2018,"lang":"en","type":"preprint","venue":"NeuroImage","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Montreal Neurological Institute and Hospital; Université de Montréal; Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Eye Institute; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; National Multiple Sclerosis Society; Genentech; Centre National de la Recherche Scientifique; Svenska Sällskapet för Medicinsk Forskning; Canada Foundation for Innovation; Ministero della Salute; National Institutes of Health; Canada Research Chairs; Intramural Research Program; Agence Nationale de la Recherche; Fondation Aix-Marseille Universite; Fondation pour l'Aide à la Recherche sur la Sclérose en Plaques; Fonds de recherche du Québec – Nature et technologies; Stockholms Läns Landsting; Wings for Life; Institut de Valorisation des Données; Fondazione Italiana Sclerosi Multipla; National Institute for Health and Care Research; Teva Pharmaceutical Industries; International Society of Regulatory Toxicology and Pharmacology; Natural Sciences and Engineering Research Council of Canada; Biogen; U.S. Department of Defense; Sanofi; EMD Serono","keywords":"Spinal cord; Segmentation; Medicine; Multiple sclerosis; Convolutional neural network; Cord; Lesion; Artificial intelligence; Pattern recognition (psychology); Computer science; Pathology; Surgery","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":[0.0005169755,0.0008882826,0.0006106651,0.001819892,0.000354664,0.001283579,0.0007180428,0.001358056,0.001206491],"category_scores_gemma":[0.001427646,0.0005917808,0.0007991929,0.0008349633,0.0003419479,0.0005739237,0.0006913811,0.0006466148,0.0005246511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008951541,"about_ca_system_score_gemma":0.001615509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.012862,"about_ca_topic_score_gemma":0.0197009,"domain_scores_codex":[0.9997554,0.00003026294,0.00001735345,0.00007285141,0.00006669873,0.00005727729],"domain_scores_gemma":[0.9996829,0.0001089453,0.00004820858,0.00005226284,0.00008128153,0.00002635174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001311871,0.0002947495,0.009343571,0.0005051593,0.0003529958,0.0009436996,0.0003086519,0.1453578,0.190412,0.005770935,0.007425782,0.6379728],"study_design_scores_gemma":[0.00002894797,0.00007009415,0.009332923,0.00005790264,0.00009125572,0.0005215081,0.00005447517,0.9229877,0.0586843,0.005382676,0.002755728,0.00003255496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4453339,0.003346425,0.5398522,0.0008675902,0.0001838405,0.0002403439,0.001353962,0.003693351,0.005128423],"genre_scores_gemma":[0.830004,0.0008710033,0.160494,0.0001751961,0.00007701005,0.00007827487,0.001525617,0.000361822,0.006412978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.012862,"threshold_uncertainty_score":0.02557427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03163840586457667,"score_gpt":0.2446892315032202,"score_spread":0.2130508256386435,"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."}}