{"id":"W2955175109","doi":"10.1109/mapr.2019.8743530","title":"Registration of Ultrasound and CBCT Images for Enhancing Tooth-Periodontinum Visualization: a Feasibility Study","year":2019,"lang":"en","type":"article","venue":"","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Visualization; Computer science; Computer vision; Image registration; 3D ultrasound; Ultrasound; Artificial intelligence; Medical physics; Computer graphics (images); Radiology; Medicine; 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":[0.004405953,0.000591052,0.0004318357,0.001080933,0.0002409726,0.0005586075,0.0008300566,0.001273059,0.001848863],"category_scores_gemma":[0.007053753,0.000602898,0.0004678518,0.0005343813,0.0005950845,0.001168858,0.0006925433,0.0003896795,0.0005371433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002185848,"about_ca_system_score_gemma":0.0007845485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001332679,"about_ca_topic_score_gemma":0.001186184,"domain_scores_codex":[0.9982918,0.0007995248,0.0001282818,0.0002102024,0.0004870338,0.00008310565],"domain_scores_gemma":[0.9961523,0.002052952,0.0001710133,0.0004423614,0.001026825,0.000154524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005141706,0.002740684,0.035972,0.001158479,0.0001990813,0.003879454,0.0011962,0.006066152,0.663059,0.001030239,0.0007362544,0.2788208],"study_design_scores_gemma":[0.002012642,0.06172685,0.1990269,0.0003067542,0.001197272,0.04153783,0.002333948,0.2218288,0.4539475,0.001310339,0.01424443,0.0005268019],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7236393,0.002161955,0.2695782,0.0003904308,0.00007836137,0.001753762,0.0001408463,0.0003652118,0.001891948],"genre_scores_gemma":[0.8026644,0.0009807871,0.1947059,0.0001075342,0.00007111103,0.0004296817,0.0001438207,0.0000809889,0.0008158064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004405953,"threshold_uncertainty_score":0.02330124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578797896617691,"score_gpt":0.3112520819252437,"score_spread":0.2954641029590668,"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."}}