{"id":"W4294975127","doi":"10.1109/embc48229.2022.9871883","title":"Deep Estimation of Speckle Statistics Parametric Images","year":2022,"lang":"en","type":"article","venue":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Speckle pattern; Parametric statistics; Nakagami distribution; Computer science; Convolutional neural network; Artificial intelligence; Envelope (radar); Pattern recognition (psychology); Parametric model; Nonparametric statistics; Algorithm; Statistics; Mathematics; Fading","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008493803,0.0007243559,0.0006526215,0.0007183586,0.0001653972,0.0006709366,0.0008093034,0.0009453883,0.0008231731],"category_scores_gemma":[0.00326579,0.0003936775,0.0005608227,0.0004269374,0.0004910174,0.0008278318,0.0008566786,0.000998166,0.0002634083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000556064,"about_ca_system_score_gemma":0.0005649558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002762129,"about_ca_topic_score_gemma":0.00305799,"domain_scores_codex":[0.9997132,0.00005378383,0.00001399386,0.00008656986,0.00008237324,0.00005012138],"domain_scores_gemma":[0.9992461,0.0003441067,0.00009761449,0.0001167851,0.0001555833,0.00003985141],"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":[0.0002683321,0.0001271618,0.004357114,0.0001300145,0.00007239097,0.0001589198,0.00009394695,0.6293518,0.05449069,0.004824068,0.002387309,0.3037383],"study_design_scores_gemma":[0.000002211884,0.00001129165,0.0004291098,0.000003403062,0.000002998619,0.00001842419,0.000003689398,0.9946688,0.00387151,0.0008344456,0.000151097,0.000003027243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09838735,0.0002484254,0.89891,0.0001945426,0.00002689648,0.00002987599,0.0002153401,0.001061548,0.000926021],"genre_scores_gemma":[0.8060951,0.0002602962,0.1906654,0.0001500762,0.00004694333,0.00006034793,0.0008661862,0.0001619907,0.001693791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002762129,"threshold_uncertainty_score":0.005492151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02208628506711992,"score_gpt":0.2980022807960365,"score_spread":0.2759159957289166,"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."}}