{"id":"W1990446781","doi":"10.1118/1.3685445","title":"Toward a practical template-based approach to semiquantitative SPECT myocardial perfusion imaging","year":2012,"lang":"en","type":"article","venue":"Medical Physics","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Single-photon emission computed tomography; Projection (relational algebra); Myocardial perfusion imaging; Nuclear medicine; Artificial intelligence; Computer science; Iterative reconstruction; Perfusion; Image processing; Spect imaging; Medical imaging; Emission computed tomography; Cardiac imaging; Computer vision; Biomedical engineering; Medicine; Image (mathematics); Algorithm; Radiology; Positron emission tomography","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":[0.002951493,0.0008214865,0.0007667694,0.001452619,0.0003390874,0.001674902,0.002270086,0.001174099,0.002306914],"category_scores_gemma":[0.007742646,0.0007659438,0.0010648,0.00106051,0.000715499,0.001075045,0.001150945,0.0007972092,0.001378011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008524594,"about_ca_system_score_gemma":0.001080249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001438011,"about_ca_topic_score_gemma":0.001530478,"domain_scores_codex":[0.9984009,0.0005242198,0.0001077937,0.0002482372,0.0006763295,0.00004250444],"domain_scores_gemma":[0.9972478,0.001022752,0.0002053885,0.0005695272,0.000856428,0.00009814309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003498191,0.0001903029,0.004345663,0.0004068478,0.0001399345,0.0003156581,0.0002433803,0.09697345,0.2113728,0.01254914,0.002287923,0.6708251],"study_design_scores_gemma":[0.00003998249,0.0002480433,0.00236739,0.00003295148,0.0000509309,0.0009124556,0.00004525893,0.9198408,0.06339504,0.006615981,0.006382484,0.0000687418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004594105,0.0001166013,0.9942887,0.00004003444,0.000007828511,0.0000636131,0.0000354969,0.0006422052,0.0002115571],"genre_scores_gemma":[0.02334493,0.0001038549,0.9759211,0.00002752596,0.00001221797,0.0001160883,0.0001079737,0.0001024947,0.0002638024],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002951493,"threshold_uncertainty_score":0.01560915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04800027044096028,"score_gpt":0.341200028333712,"score_spread":0.2931997578927518,"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."}}