{"id":"W3031818993","doi":"10.1186/s12938-020-00778-z","title":"Clutter suppression in ultrasound: performance evaluation and review of low-rank and sparse matrix decomposition methods","year":2020,"lang":"en","type":"review","venue":"BioMedical Engineering OnLine","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Clutter; Singular value decomposition; Computer science; Robustness (evolution); Matrix decomposition; Rank (graph theory); Robust principal component analysis; Matrix completion; Artificial intelligence; Sparse matrix; Pattern recognition (psychology); Low-rank approximation; Visualization; Algorithm; Principal component analysis; Mathematics; Radar; Physics","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":[0.001022201,0.000332525,0.001533335,0.0004244353,0.0000180642,0.000009453152,0.00007959011,0.0002350315,0.00003925084],"category_scores_gemma":[0.0007774997,0.0002550313,0.000170204,0.0006404161,0.0001004125,0.000062769,0.00004765104,0.000544741,0.000001798137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007026613,"about_ca_system_score_gemma":0.0001391825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004874634,"about_ca_topic_score_gemma":1.278267e-7,"domain_scores_codex":[0.9980316,0.0001495996,0.0008166456,0.0003761652,0.0004074934,0.0002184767],"domain_scores_gemma":[0.9989053,0.0004073416,0.0001781048,0.0002098284,0.0000639737,0.000235421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001237596,0.0001101173,0.00003526389,0.1924752,0.00007676927,0.00000404313,0.00002624494,0.000001568332,0.000573675,9.927074e-7,0.000161219,0.8065225],"study_design_scores_gemma":[0.0006364464,0.0001652775,0.0005217037,0.2574269,0.001129293,0.0004119711,0.000002991199,0.004134878,0.000008277458,0.000001140247,0.7353306,0.0002305654],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008790226,0.9955282,0.002316492,0.0002746522,0.0001601961,0.0007417765,0.0000482983,0.00004600202,0.000005333652],"genre_scores_gemma":[0.00008734054,0.9464516,0.05217525,0.00009747418,0.0001863649,0.00003983126,0.0009160825,0.00004074705,0.000005293318],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.806292,"threshold_uncertainty_score":0.9999902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02286018134451782,"score_gpt":0.3909215990139938,"score_spread":0.3680614176694759,"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."}}