{"id":"W2619398955","doi":"10.1007/978-3-319-59876-5_47","title":"Mesh-Based Active Model Initialization for Multiple Organ Segmentation in MR Images","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Initialization; Computer science; Segmentation; Active contour model; Artificial intelligence; Image segmentation; Computer vision; Scale-space segmentation; Convergence (economics); Pattern recognition (psychology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008171612,0.001046361,0.001365728,0.001174142,0.0005307359,0.001906264,0.00244241,0.002296962,0.005309369],"category_scores_gemma":[0.002291469,0.001301058,0.001804467,0.001483439,0.000550773,0.00132449,0.001722744,0.002318768,0.003216821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007973266,"about_ca_system_score_gemma":0.001043558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003468186,"about_ca_topic_score_gemma":0.00569267,"domain_scores_codex":[0.9995109,0.0001116599,0.00003533771,0.0001034203,0.0001942585,0.00004444651],"domain_scores_gemma":[0.9992753,0.0003561447,0.00005831038,0.0001370101,0.0001403035,0.00003303286],"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":[0.0002762114,0.00009909948,0.0004982286,0.0004508235,0.0001896931,0.0001909588,0.0002643719,0.3412875,0.0556005,0.01384678,0.01265141,0.5746444],"study_design_scores_gemma":[0.000008935036,0.00002054128,0.0001502711,0.0000246128,0.00002395373,0.0001010431,0.00001684544,0.9805028,0.0107054,0.004502956,0.003924413,0.00001821294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001552679,0.0002346715,0.996298,0.00005569814,0.00004590754,0.00003082128,0.00006070207,0.001080153,0.0006414339],"genre_scores_gemma":[0.07145271,0.0007122187,0.9204205,0.0001475801,0.00008414198,0.0002079198,0.0006971182,0.001433875,0.004844043],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005309369,"threshold_uncertainty_score":0.01776165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03212577520410622,"score_gpt":0.3132348175231423,"score_spread":0.2811090423190361,"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."}}