{"id":"W2013627343","doi":"10.1118/1.4773873","title":"2D-3D rigid registration to compensate for prostate motion during 3D TRUS-guided biopsy","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University; Robarts Clinical Trials","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Fiducial marker; Prostate biopsy; Image registration; 3D ultrasound; Computer vision; Computer science; Artificial intelligence; Medical imaging; Prostate; Metric (unit); Ultrasound; Medicine; Radiology; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001283858,0.0001732276,0.0003026685,0.00003142642,0.00009829472,0.00003448733,0.00006803413,0.00007406007,0.0001583103],"category_scores_gemma":[0.0001292138,0.000136064,0.00008502321,0.0001452253,0.00006354323,0.0001192195,0.00002963617,0.0001177176,0.0001682803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001869388,"about_ca_system_score_gemma":0.0001054919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001638596,"about_ca_topic_score_gemma":0.00000695246,"domain_scores_codex":[0.9985546,0.00001804561,0.0003215877,0.0003285212,0.0004584299,0.0003187957],"domain_scores_gemma":[0.9990291,0.00005094415,0.00009516803,0.0002644337,0.0001750611,0.0003853136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009141258,0.004068296,0.06819748,0.002326687,0.0007153466,0.0002480957,0.002790121,0.0001733539,0.03357152,0.002808688,0.059395,0.8247913],"study_design_scores_gemma":[0.03293994,0.004805998,0.4399489,0.003104378,0.0008869867,0.0002246874,0.0002239368,0.01324105,0.4619502,0.01363113,0.02732072,0.001722031],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745963,0.00006558084,0.01101788,0.01034197,0.0003023364,0.002412266,0.00003618606,0.00011359,0.001113912],"genre_scores_gemma":[0.9948868,0.00006948991,0.001795328,0.001068609,0.0006006471,0.0008551679,0.0002223489,0.00003194747,0.0004697025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8230693,"threshold_uncertainty_score":0.5548527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02751729075679065,"score_gpt":0.298722647017183,"score_spread":0.2712053562603924,"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."}}