{"id":"W2009766183","doi":"10.1118/1.4722983","title":"Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging","year":2012,"lang":"en","type":"article","venue":"Medical Physics","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Myocardial perfusion imaging; Iterative reconstruction; Medical imaging; Noise (video); Nuclear medicine; Medical physics; Perfusion scanning; Medicine; Radiology; Computer science; Image (mathematics); Perfusion; Computer vision","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007113847,0.0001163595,0.0003660246,0.0000340636,0.00004225035,0.0000103485,0.00003943655,0.00003182008,0.00006648903],"category_scores_gemma":[0.001704337,0.00007197326,0.0001368824,0.0001054245,0.0006847555,0.0001086372,0.00006413486,0.0003546445,0.00001038022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006470773,"about_ca_system_score_gemma":0.0001564342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001738786,"about_ca_topic_score_gemma":0.000003863076,"domain_scores_codex":[0.9988829,0.00009812983,0.0002405858,0.0001195732,0.0004055284,0.0002532996],"domain_scores_gemma":[0.9988673,0.0006122967,0.00005984274,0.0001653094,0.00005778921,0.0002374529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002729543,0.0001738113,0.755751,0.00003408058,0.00002535619,0.00002374123,0.0003185527,0.000002148197,0.0002381084,0.0002599293,0.0005478699,0.2423525],"study_design_scores_gemma":[0.00548772,0.00005825633,0.981886,0.0001521068,0.0001526933,0.0004142163,0.00009411235,0.009329171,0.0008945686,0.001380857,0.00002739992,0.000122874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731029,0.0002143346,0.02310863,0.0004750408,0.0003571452,0.0002161106,0.00003115217,0.00001875809,0.002475946],"genre_scores_gemma":[0.9985973,0.00007245717,0.0003118696,0.0001124727,0.0008608223,0.000005405617,0.00002472241,0.00001189108,0.0000031235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2422296,"threshold_uncertainty_score":0.2934985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006660711069574881,"score_gpt":0.2833949821441353,"score_spread":0.2767342710745604,"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."}}