{"id":"W2163482106","doi":"10.1109/tns.2005.858208","title":"A robust visual tracking system for patient motion detection in SPECT: hardware solutions","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Nuclear Science","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Computer vision; Imaging phantom; Computer science; Tracking (education); Artificial intelligence; Calibration; Tracking system; Match moving; Synchronization (alternating current); Visualization; Motion (physics); Computer graphics (images); Filter (signal processing); Physics; Optics; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002473241,0.0007029464,0.0006966631,0.001206317,0.0003060484,0.001420125,0.002186829,0.001228581,0.005075152],"category_scores_gemma":[0.004488619,0.0006628853,0.000522114,0.0009018746,0.000422148,0.001456344,0.001127663,0.0006834425,0.002333881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007941835,"about_ca_system_score_gemma":0.001182638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001865999,"about_ca_topic_score_gemma":0.001779222,"domain_scores_codex":[0.9985352,0.0002685131,0.0001119256,0.0002949049,0.0007099417,0.00007955945],"domain_scores_gemma":[0.9985189,0.000316387,0.0001775793,0.0003133052,0.0005921161,0.00008177029],"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":[0.000725685,0.0001137735,0.002853173,0.0003434482,0.0001106052,0.0002197308,0.0001227735,0.01094533,0.4601968,0.00350327,0.005235965,0.5156295],"study_design_scores_gemma":[0.0004160269,0.002670614,0.01558381,0.0002206482,0.0003624444,0.003358711,0.0001081362,0.349307,0.5701185,0.003902677,0.05360343,0.0003479791],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006114524,0.0001940392,0.9897925,0.0001134372,0.0000509723,0.0001070719,0.00009649569,0.00299884,0.000532119],"genre_scores_gemma":[0.08808131,0.0002910596,0.9081384,0.0001978229,0.00008745782,0.0002771484,0.0004804986,0.0003941159,0.002052278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005075152,"threshold_uncertainty_score":0.01697809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03861122345115406,"score_gpt":0.2927527585623705,"score_spread":0.2541415351112164,"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."}}