{"id":"W4210354887","doi":"10.1121/10.0009385","title":"Decorrelated compounding improves lesion signal-to-noise ratio of low-contrast lesions in synthetic transmit aperture ultrasound imaging","year":2022,"lang":"en","type":"article","venue":"JASA Express Letters","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Decorrelation; Speckle pattern; Compounding; Contrast-to-noise ratio; Contrast (vision); Signal-to-noise ratio (imaging); Speckle noise; Noise (video); Lesion; SIGNAL (programming language); Ultrasound; Computer science; Materials science; Optics; Artificial intelligence; Image quality; Physics; Computer vision; Acoustics; Medicine; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003630293,0.0003064438,0.0005214271,0.0006797581,0.0002970771,0.00004720376,0.0002585113,0.00005321399,0.0002031933],"category_scores_gemma":[0.0001417035,0.0002994458,0.0002512093,0.0007015364,0.0001456567,0.0001773116,0.00005518816,0.0005768723,0.000009177051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001567413,"about_ca_system_score_gemma":0.00006057298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002005451,"about_ca_topic_score_gemma":0.000006441828,"domain_scores_codex":[0.9976393,0.0002050685,0.0005857187,0.0005364067,0.0005013755,0.0005321546],"domain_scores_gemma":[0.998304,0.0008966954,0.0001478891,0.0004060153,0.00004675253,0.0001986436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003914106,0.0003465118,0.02597426,0.0001166225,0.00005505145,0.00004157041,0.002797167,0.002246451,0.9651052,0.000009868631,0.001608471,0.001307434],"study_design_scores_gemma":[0.0358473,0.002477968,0.4691527,0.009446468,0.001959545,0.002866667,0.03324517,0.04436369,0.3260952,0.0002883868,0.06801904,0.006237893],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784114,0.0002957192,0.01577958,0.00420469,0.0003040493,0.0006621504,0.00005009667,0.0001118916,0.0001803538],"genre_scores_gemma":[0.9921638,0.00001972742,0.002189432,0.005236303,0.00006358301,0.0001201851,0.00008105669,0.00006412782,0.0000617881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.63901,"threshold_uncertainty_score":0.9999458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007010930722148079,"score_gpt":0.2271739817853394,"score_spread":0.2201630510631913,"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."}}