{"id":"W2960916785","doi":"10.1109/isbi.2019.8759543","title":"Suppressing Clutter Components In Ultrasound Color Flow Imaging Using Robust Matrix Completion Algorithm: Simulation And Phantom Study","year":2019,"lang":"en","type":"article","venue":"","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Clutter; Singular value decomposition; Imaging phantom; Computer science; Algorithm; Computer vision; Artificial intelligence; Matrix (chemical analysis); Constant false alarm rate; Computation; Matrix decomposition; Eigendecomposition of a matrix; Pattern recognition (psychology); Eigenvalues and eigenvectors; Radar; Physics; Optics; Materials science","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":[0.001066145,0.0006543364,0.0005102472,0.0006836284,0.0001847948,0.0004714435,0.0004884597,0.0008527149,0.0007840815],"category_scores_gemma":[0.002896377,0.0002139901,0.0005435608,0.0005605155,0.0005181728,0.0006555452,0.0003921391,0.0004224648,0.0001269665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002927958,"about_ca_system_score_gemma":0.0003933567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003002463,"about_ca_topic_score_gemma":0.00156942,"domain_scores_codex":[0.9996079,0.0001521061,0.00001748693,0.00003409974,0.0001413101,0.00004708116],"domain_scores_gemma":[0.9981335,0.001236943,0.0001713321,0.000107178,0.0002953915,0.00005561385],"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":[0.0008775278,0.000478123,0.005334158,0.000557022,0.0001172073,0.0009539925,0.0004920225,0.8471807,0.06759523,0.005660515,0.002190835,0.06856268],"study_design_scores_gemma":[0.00004326204,0.0003310803,0.0009235472,0.00001679472,0.00002249084,0.0002478297,0.00004426136,0.986312,0.01076968,0.0005856424,0.0006800076,0.00002346815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4627091,0.001689558,0.5294353,0.0006471362,0.00008933184,0.000184476,0.000182694,0.001125248,0.003937178],"genre_scores_gemma":[0.8739877,0.0009283859,0.123111,0.0001618002,0.00002724354,0.000116569,0.0002290462,0.0001037161,0.001334584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003002463,"threshold_uncertainty_score":0.005970001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03175206426279797,"score_gpt":0.3096865170747707,"score_spread":0.2779344528119727,"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."}}