{"id":"W2034703003","doi":"10.1118/1.4822514","title":"Fully 3D iterative CT reconstruction using polar coordinates","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Iterative reconstruction; Polar coordinate system; Computed tomography; Medical imaging; Iterative method; Polar; Computer vision; Computer science; Artificial intelligence; Algorithm; Physics; Mathematics; Radiology; Geometry; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003670582,0.0006029368,0.000254139,0.0003331396,0.0001801245,0.0008430001,0.0004053304,0.0003393612,0.002360981],"category_scores_gemma":[0.001493962,0.0003991788,0.0004686175,0.0004345015,0.0003269272,0.0005018663,0.0007284567,0.0004057524,0.0008917422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000216613,"about_ca_system_score_gemma":0.0006897489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001398353,"about_ca_topic_score_gemma":0.001419271,"domain_scores_codex":[0.9997619,0.00006859326,0.00001588941,0.00002745517,0.0001151327,0.00001105521],"domain_scores_gemma":[0.9995176,0.0002132662,0.00004880335,0.00008557041,0.0001199308,0.00001481002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007011895,0.0000603844,0.006097004,0.0006768827,0.0001417497,0.001368292,0.0004693629,0.4759721,0.2698891,0.02810287,0.002954064,0.213567],"study_design_scores_gemma":[0.00004062563,0.0001360571,0.001579741,0.00006501003,0.00004356084,0.002146569,0.00006528613,0.8776218,0.1055311,0.005002829,0.007720408,0.00004708379],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01044369,0.0001134862,0.9877678,0.00004182774,0.000007354609,0.00002342299,0.00006307801,0.000324614,0.001214672],"genre_scores_gemma":[0.2472429,0.0007144008,0.7494119,0.00004714586,0.00001169752,0.00009787425,0.000402996,0.0002813779,0.001789646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002360981,"threshold_uncertainty_score":0.007898211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02369005327879904,"score_gpt":0.311403037846173,"score_spread":0.2877129845673739,"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."}}