{"id":"W2306943469","doi":"10.1117/12.2217342","title":"Accurate quantification of local changes for carotid arteries in 3D ultrasound images using convex optimization-based deformable registration","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials; University of Calgary","funders":"","keywords":"Carotid arteries; 3D ultrasound; Image registration; Ultrasound; Computer vision; Computer science; Artificial intelligence; Radiology; Medicine; Cardiology; Image (mathematics)","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":[0.001181436,0.0007192009,0.0007676233,0.001274014,0.0003017071,0.0008868855,0.0006507213,0.0007453244,0.0007923518],"category_scores_gemma":[0.004259406,0.0005073284,0.0009060951,0.000909601,0.0005338905,0.0007878494,0.0009764117,0.0007403557,0.0004319042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005334147,"about_ca_system_score_gemma":0.0009054655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003009711,"about_ca_topic_score_gemma":0.004187874,"domain_scores_codex":[0.9991776,0.0002011923,0.00006326904,0.0002138562,0.0002937059,0.00005037431],"domain_scores_gemma":[0.9992763,0.0002642199,0.0001413367,0.0001426899,0.000152757,0.00002281979],"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":[0.0003848155,0.0001768477,0.00583882,0.0002483107,0.0002555207,0.0002831015,0.0004168602,0.3403563,0.2533283,0.004542496,0.001519191,0.3926494],"study_design_scores_gemma":[0.00001104379,0.00008567853,0.006673373,0.00001170778,0.00004783554,0.0002661892,0.00003959799,0.9369052,0.05280927,0.001775355,0.001325574,0.00004910935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07557986,0.0003296443,0.9222997,0.0001037499,0.00002579808,0.0000838934,0.0001012056,0.0007609755,0.0007152656],"genre_scores_gemma":[0.4557026,0.0004821444,0.5414673,0.00007239616,0.00002613936,0.0001949982,0.0003255063,0.0002922759,0.001436565],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003009711,"threshold_uncertainty_score":0.006248116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01606881444046915,"score_gpt":0.2443641049041852,"score_spread":0.228295290463716,"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."}}