{"id":"W2046303004","doi":"10.1007/s11548-010-0535-3","title":"New prototype neuronavigation system based on preoperative imaging and intraoperative freehand ultrasound: system description and validation","year":2010,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Canadian Institutes of Health Research","keywords":"Neuronavigation; Fiducial marker; Ultrasound; Computer science; 3D ultrasound; Artificial intelligence; Computer vision; Calibration; Image registration; Image-guided surgery; Medicine; Patient registration; Feature (linguistics); Navigation system; Radiology; Magnetic resonance imaging; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001029869,0.0007511181,0.000954071,0.000663134,0.0004391671,0.0007352364,0.001669834,0.001137511,0.003452126],"category_scores_gemma":[0.001376037,0.0004928295,0.0002786349,0.0003579079,0.0004945945,0.0007021965,0.0008375536,0.0004574266,0.0009189459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006009584,"about_ca_system_score_gemma":0.001938488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004156257,"about_ca_topic_score_gemma":0.005808816,"domain_scores_codex":[0.9994672,0.00009750563,0.00004652423,0.0001331705,0.0002144121,0.00004125437],"domain_scores_gemma":[0.9988694,0.0002783698,0.00005799593,0.0001483694,0.0005262594,0.0001196272],"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":[0.002825028,0.0005050682,0.02333471,0.001357719,0.0003289517,0.001150381,0.0009995081,0.01009852,0.4532181,0.001728885,0.006741947,0.4977112],"study_design_scores_gemma":[0.001373413,0.00774177,0.07259063,0.0003491307,0.001702064,0.02286604,0.0008031533,0.2385983,0.5970144,0.002352294,0.05394533,0.0006633536],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1615231,0.0009383456,0.8251951,0.0002857971,0.0002561292,0.001179751,0.0006290178,0.008140019,0.001852757],"genre_scores_gemma":[0.4298475,0.0006264464,0.5608342,0.0004104096,0.00006137744,0.001260468,0.0008756274,0.0004276987,0.005656318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004156257,"threshold_uncertainty_score":0.01154852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01189795008052474,"score_gpt":0.2566762314369603,"score_spread":0.2447782813564356,"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."}}