{"id":"W4413146596","doi":"10.1109/sas65169.2025.11105208","title":"Confidence-Aware 3D Spatial Compounding of 2D Ultrasound Images for Needle Shadow Removal","year":2025,"lang":"en","type":"article","venue":"","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Compounding; Shadow (psychology); Computer science; Computer vision; Ultrasound; Artificial intelligence; Computer graphics (images); Radiology; Materials science; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004927034,0.0007608232,0.0005195187,0.000832618,0.0002126833,0.0007838685,0.0005786496,0.0005748363,0.001206104],"category_scores_gemma":[0.002502193,0.0004427042,0.0006515817,0.0005616385,0.000380026,0.0009175508,0.001279698,0.0006202996,0.0004011635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003121607,"about_ca_system_score_gemma":0.0007497418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001137413,"about_ca_topic_score_gemma":0.001675295,"domain_scores_codex":[0.9995375,0.00007191148,0.00002698178,0.00005987026,0.0002711288,0.00003279346],"domain_scores_gemma":[0.9990568,0.0003183995,0.0002066359,0.0001277172,0.0002359692,0.00005455153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003945979,0.0001046389,0.002888661,0.0002641497,0.0001163657,0.0002961587,0.0002413335,0.170771,0.3025762,0.004881857,0.001461697,0.5160033],"study_design_scores_gemma":[0.00001528154,0.00009898801,0.001649007,0.00001071293,0.00003625252,0.000360805,0.0000236236,0.9313959,0.06256279,0.00132134,0.002489455,0.0000358394],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02303966,0.0001594388,0.9759315,0.00005827285,0.00001771995,0.00002879704,0.00002661897,0.0003713709,0.0003666885],"genre_scores_gemma":[0.3034121,0.0004065561,0.6942381,0.00009299184,0.00005206489,0.00008141287,0.0001974541,0.0002460461,0.0012732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001206104,"threshold_uncertainty_score":0.004034817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007776189998033118,"score_gpt":0.2373029192016209,"score_spread":0.2295267292035878,"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."}}