{"id":"W2090212158","doi":"10.1117/12.2008408","title":"Modeling and control of nonstationary noise characteristics in filtered-backprojection and penalized likelihood image reconstruction","year":2013,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Cancer Institute","keywords":"Noise (video); Iterative reconstruction; Computer science; Artificial intelligence; Image (mathematics); Maximum likelihood; Noise measurement; Computer vision; Pattern recognition (psychology); Algorithm; Mathematics; Statistics; Noise reduction","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":[0.0003594662,0.000162005,0.0003659265,0.0001113673,0.0000367285,0.00004020106,0.0001403201,0.000113669,0.00001278908],"category_scores_gemma":[0.0004961618,0.0001354145,0.000150452,0.0001599111,0.0002198682,0.0003513772,0.00005501014,0.0002273964,3.05931e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005702019,"about_ca_system_score_gemma":0.00002943917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004993198,"about_ca_topic_score_gemma":9.75338e-8,"domain_scores_codex":[0.9986702,2.382288e-8,0.0006233357,0.0002404033,0.0002826579,0.0001834162],"domain_scores_gemma":[0.9984037,0.00009400274,0.0002379189,0.00003789267,0.001126586,0.00009995932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001058829,0.0001185503,0.003813553,0.000735254,0.000120141,6.050366e-8,0.0001232215,0.000003934344,0.9572733,0.03545263,0.0002685128,0.001984951],"study_design_scores_gemma":[0.002864633,0.0003400909,0.01108769,0.001054422,0.0002296662,0.000105899,0.0009988786,0.9326261,0.04700718,0.003331559,0.0001003273,0.0002536004],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942127,0.0000399347,0.0008934409,0.003679463,0.00004164338,0.0008291922,0.00003045516,0.00004007055,0.0002330507],"genre_scores_gemma":[0.8114623,0.0001917544,0.1879475,0.00007305913,0.00009043863,0.0001887141,0.000009034301,0.00002056621,0.00001656997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9326221,"threshold_uncertainty_score":0.5522045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009810428415619733,"score_gpt":0.242929083111102,"score_spread":0.2331186546954822,"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."}}