{"id":"W4406891930","doi":"10.1109/jbhi.2025.3535541","title":"Coarse for Fine: Bounding Box Supervised Thyroid Ultrasound Image Segmentation Using Spatial Arrangement and Hierarchical Prediction Consistency","year":2025,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"AI in cancer detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Minimum bounding box; Segmentation; Artificial intelligence; Computer science; Image segmentation; Pattern recognition (psychology); Consistency (knowledge bases); Computer vision; Bounding overwatch; Image (mathematics)","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":[0.001211459,0.0009092574,0.00128051,0.0006184516,0.0004642679,0.001164486,0.002243865,0.001458437,0.001675289],"category_scores_gemma":[0.003816756,0.0005566844,0.0008672754,0.0005575037,0.001139873,0.00150725,0.001762779,0.001245397,0.0006034013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008880587,"about_ca_system_score_gemma":0.001464667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005506591,"about_ca_topic_score_gemma":0.005801594,"domain_scores_codex":[0.9992343,0.0001540305,0.000036987,0.0003034055,0.0001807336,0.00009056214],"domain_scores_gemma":[0.9986766,0.0005257796,0.0001770753,0.0002316083,0.0002915632,0.00009737974],"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":[0.0005061089,0.0001439037,0.004392728,0.0001323533,0.00009928071,0.0001591353,0.0002395654,0.6839812,0.02479629,0.007896271,0.003733418,0.2739198],"study_design_scores_gemma":[0.000006564137,0.00002277096,0.0002470714,0.0000047005,0.000007499639,0.00001763058,0.000006124314,0.9956036,0.001674025,0.00220415,0.0002008288,0.000005079797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04099663,0.0001967675,0.9558703,0.0001846886,0.00002453939,0.00005836244,0.00008446979,0.001350465,0.001233821],"genre_scores_gemma":[0.808012,0.0001655015,0.1859505,0.0003741539,0.00007779575,0.0001687691,0.0005763935,0.0004031088,0.004271707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005506591,"threshold_uncertainty_score":0.01094913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0300507028653224,"score_gpt":0.3235242563556821,"score_spread":0.2934735534903597,"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."}}