{"id":"W4403090349","doi":"10.1007/978-3-031-72069-7_26","title":"Masked Residual Diffusion Probabilistic Model with Regional Asymmetry Prior for Generating Perfusion Maps from Multi-phase CTA","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Residual; Diffusion; Asymmetry; Probabilistic logic; Perfusion; Algorithm; Artificial intelligence; Radiology; Thermodynamics; Physics; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006830326,0.0007340391,0.0006482524,0.0005174261,0.0006031478,0.0009599663,0.001995847,0.0003533615,0.000007860545],"category_scores_gemma":[0.0001277447,0.0005601741,0.0001752991,0.0004466896,0.0005316822,0.0005464543,0.001263263,0.0007158319,0.00001124602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003016032,"about_ca_system_score_gemma":0.0007300128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000375921,"about_ca_topic_score_gemma":0.0002360329,"domain_scores_codex":[0.9951962,0.00004972874,0.0006111118,0.002443066,0.0009958977,0.0007040253],"domain_scores_gemma":[0.9972444,0.000689827,0.0003023152,0.001173308,0.0003799703,0.0002101896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008299781,0.0001384071,0.000006745864,0.00008041004,0.00003309947,0.00007714653,0.001115608,0.6585087,0.00421862,0.008115998,0.000228256,0.3273941],"study_design_scores_gemma":[0.0009407346,0.0003281113,0.000006262394,0.0006852205,0.00003830321,0.00001826732,5.869588e-7,0.9379345,0.001147473,0.05783756,0.0003691218,0.0006938542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006200054,0.0005982375,0.9952186,0.001108916,0.001018068,0.001053906,0.00007660489,0.0001567442,0.0001489257],"genre_scores_gemma":[0.03311852,0.00002787804,0.9638096,0.000748331,0.001214635,0.00004705893,0.00006649376,0.00007074216,0.0008967338],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3267002,"threshold_uncertainty_score":0.999685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02888053999355573,"score_gpt":0.2626765741180401,"score_spread":0.2337960341244844,"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."}}