{"id":"W2117684737","doi":"10.1109/isbi.2011.5872349","title":"Coupled level set approach to segment carotid arteries from 3D ultrasound images","year":2011,"lang":"en","type":"article","venue":"","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Boundary (topology); Level set (data structures); Segmentation; Computer vision; Ultrasound; Computation; Image segmentation; Artificial intelligence; Computer science; 3D ultrasound; Energy (signal processing); Lumen (anatomy); Transverse plane; Mathematics; Algorithm; Pattern recognition (psychology); Physics; Mathematical analysis; Anatomy; Acoustics; Medicine; Statistics; Surgery","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":[0.002289643,0.001163691,0.00113361,0.002521242,0.0006078688,0.00177059,0.002387019,0.00175165,0.00189798],"category_scores_gemma":[0.005211096,0.001209043,0.002077682,0.0009590261,0.0008670498,0.00113964,0.001688507,0.001230371,0.001038079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001421548,"about_ca_system_score_gemma":0.001507839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0043095,"about_ca_topic_score_gemma":0.005603149,"domain_scores_codex":[0.9981281,0.000479623,0.0001332543,0.0002355914,0.0009520979,0.00007132945],"domain_scores_gemma":[0.9977905,0.001046836,0.0002070652,0.0003030006,0.0005924735,0.00006012125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001606697,0.000132542,0.001967779,0.0002706146,0.0003932275,0.0001881874,0.0003420221,0.5792274,0.0561318,0.01014517,0.001334913,0.3497056],"study_design_scores_gemma":[0.000008742242,0.00003673762,0.0003398771,0.00001129667,0.00002700636,0.00008613944,0.00001176896,0.9859771,0.0101296,0.002079702,0.001265966,0.00002625129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00369842,0.00005411663,0.9955338,0.00002604818,0.000009325788,0.00004165398,0.00001479198,0.0003742243,0.0002475218],"genre_scores_gemma":[0.06820638,0.0001138814,0.9301751,0.00007132511,0.00001781283,0.0001958312,0.0001184502,0.0002202233,0.0008811193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0043095,"threshold_uncertainty_score":0.01210892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04611771349966476,"score_gpt":0.2466685493270834,"score_spread":0.2005508358274186,"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."}}