{"id":"W2059048282","doi":"10.1117/12.2043659","title":"Visualizing positional uncertainty in freehand 3D ultrasound","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer vision; Computer science; Artificial intelligence; Image plane; Pixel; Voxel; Position (finance); Rendering (computer graphics); Orientation (vector space); Covariance; Point cloud; Monte Carlo method; Covariance matrix; Algorithm; Image (mathematics); Mathematics; Geometry; Statistics","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":[0.001323572,0.0007854421,0.0006023449,0.001678092,0.0003477933,0.001897458,0.0008470939,0.001131242,0.001797732],"category_scores_gemma":[0.006601338,0.0006992628,0.0006630408,0.0008268148,0.0008125555,0.001559525,0.001868705,0.0006844638,0.0002352201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009114532,"about_ca_system_score_gemma":0.0009841435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005779461,"about_ca_topic_score_gemma":0.004418339,"domain_scores_codex":[0.9986413,0.000331318,0.00005445634,0.0001153952,0.0007627763,0.00009479357],"domain_scores_gemma":[0.9972114,0.001973858,0.0002299421,0.0002129113,0.000299483,0.00007246727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003329985,0.00006186179,0.003400112,0.0002132729,0.00007852428,0.0008378691,0.001212419,0.8391952,0.03690451,0.01636319,0.001040401,0.1003597],"study_design_scores_gemma":[0.00002324883,0.00009623329,0.002550111,0.00004125481,0.00002079754,0.0004464047,0.0001515665,0.968186,0.0159049,0.01040672,0.002100238,0.00007259651],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09914993,0.0004800466,0.8966234,0.0001775406,0.00003282958,0.00005036743,0.0001574875,0.001707517,0.001620859],"genre_scores_gemma":[0.7927877,0.0004775186,0.2047044,0.00007907006,0.00004215956,0.00006846259,0.0002034542,0.0004898312,0.001147453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005779461,"threshold_uncertainty_score":0.01149166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008611381407354023,"score_gpt":0.220325008866549,"score_spread":0.211713627459195,"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."}}