{"id":"W2018085986","doi":"10.1118/1.3062875","title":"A local shift‐variant Fourier model and experimental validation of circular cone‐beam computed tomography artifacts","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Ontario Institute for Cancer Research; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute; National Institutes of Health","keywords":"Cone beam computed tomography; Image-guided radiation therapy; Physics; Optics; Rotation (mathematics); Ligand cone angle; Oblique case; Beam (structure); Field of view; Iterative reconstruction; Geometry; Medical imaging; Mathematics; Computed tomography; Artificial intelligence; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001868123,0.0001246159,0.0002886968,0.00003946203,0.00004168081,0.000008972762,0.00008944097,0.0001071546,0.00005974066],"category_scores_gemma":[0.00004690632,0.0001055286,0.00008130247,0.000195983,0.0003227625,0.00005312383,0.00003813776,0.0002303498,0.000003914779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001990226,"about_ca_system_score_gemma":0.00009410521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001139152,"about_ca_topic_score_gemma":8.29968e-8,"domain_scores_codex":[0.9986851,0.00001758228,0.0002819911,0.0002284752,0.0006093514,0.0001775677],"domain_scores_gemma":[0.9992025,0.00003761339,0.00007117867,0.0002585176,0.00005317558,0.0003770375],"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":[0.0009564229,0.02678598,0.004278942,0.001395305,0.0009860025,0.0007688219,0.007038643,0.001963101,0.3379305,0.1540857,0.07463893,0.3891717],"study_design_scores_gemma":[0.002611716,0.0005647626,0.001720385,0.0004213941,0.0001681091,0.00007443767,0.00004485725,0.3829069,0.5713443,0.03909359,0.0007334822,0.0003161065],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3420752,0.00009153077,0.65289,0.004189064,0.00001942504,0.0002672946,0.000004209295,0.00009707334,0.0003662401],"genre_scores_gemma":[0.9907625,0.000009874286,0.007010181,0.002021089,0.00009876167,0.00001343431,0.00006496856,0.0000109682,0.000008253313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6486872,"threshold_uncertainty_score":0.4303331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02363923295386678,"score_gpt":0.30151233862203,"score_spread":0.2778731056681632,"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."}}