{"id":"W2027361807","doi":"10.1016/j.compmedimag.2013.06.007","title":"Synchronized 2D/3D optical mapping for interactive exploration and real-time visualization of multi-function neurological images","year":2013,"lang":"en","type":"article","venue":"Computerized Medical Imaging and Graphics","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"CancerCare Manitoba; University of Winnipeg; Centre for Imaging Technology Commercialization; Western University","funders":"","keywords":"Computer science; Visualization; Software; Volume rendering; Rendering (computer graphics); Interactivity; Artificial intelligence; Computer vision; Data visualization; Interactive visualization; Image processing; Computer graphics (images); Image (mathematics); Multimedia","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":[0.0004077029,0.0007869765,0.0003983951,0.001162935,0.0002825328,0.0008968004,0.0007129846,0.0004279972,0.0144546],"category_scores_gemma":[0.001478253,0.0005458934,0.0003671357,0.0007974607,0.0002657345,0.0006652695,0.00173215,0.0004659882,0.0009130999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002254424,"about_ca_system_score_gemma":0.0006992465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001226749,"about_ca_topic_score_gemma":0.002562907,"domain_scores_codex":[0.99983,0.00004785684,0.00001128663,0.00002397046,0.00005935898,0.00002749173],"domain_scores_gemma":[0.9995704,0.0002357533,0.00002758125,0.00007050409,0.00004746879,0.00004838956],"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":[0.001657735,0.0001777063,0.002416609,0.000762941,0.0001239614,0.001019938,0.00109033,0.02688499,0.4452819,0.006399924,0.01574684,0.4984371],"study_design_scores_gemma":[0.0005445897,0.0007084847,0.01883828,0.0002743306,0.000211615,0.004994084,0.0008596636,0.5284044,0.3612376,0.01407716,0.06951593,0.0003339841],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04530917,0.0004034498,0.9436618,0.0001959023,0.00009942512,0.0002159503,0.0005738849,0.00500012,0.004540154],"genre_scores_gemma":[0.3190303,0.0006211501,0.6743342,0.0001412129,0.00008141129,0.00050671,0.0004908533,0.001643787,0.003150369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0144546,"threshold_uncertainty_score":0.04835546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02090665674447465,"score_gpt":0.2984976817356936,"score_spread":0.2775910249912189,"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."}}