{"id":"W1596933240","doi":"10.1109/iembs.2003.1279808","title":"Fast reconstruction of volumetric models of anatomical structures","year":2004,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Delaunay triangulation; Computer vision; Artificial intelligence; Computer science; Triangulation; 3D reconstruction; Segmentation; Surface reconstruction; Smoothing; Process (computing); Constrained Delaunay triangulation; Visual hull; Iterative reconstruction; Tetrahedron; Image segmentation; Marching cubes; Algorithm; Mathematics; Surface (topology); Visualization; Geometry","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":[0.0007905504,0.0009387159,0.0008962998,0.001416513,0.0002723256,0.001409478,0.001532286,0.001236185,0.002375462],"category_scores_gemma":[0.003652388,0.001476969,0.001635002,0.000950232,0.0005468123,0.001301371,0.001792314,0.001512627,0.001706896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004402393,"about_ca_system_score_gemma":0.0008499277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001751956,"about_ca_topic_score_gemma":0.002141445,"domain_scores_codex":[0.9990166,0.0001587474,0.00004416895,0.00009465934,0.0006363918,0.00004931107],"domain_scores_gemma":[0.9989082,0.0004566794,0.0001074843,0.0003165743,0.0001715295,0.00003956879],"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":[0.000147806,0.00004310549,0.0008021831,0.0003353748,0.0001497995,0.0004437287,0.0002665107,0.6062229,0.0555686,0.02044843,0.006070234,0.3095014],"study_design_scores_gemma":[0.00001761619,0.00004771014,0.0003450065,0.00002979912,0.00002181402,0.0007399615,0.00003789175,0.9648089,0.01543695,0.008660606,0.009811151,0.00004253346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002108738,0.00008818309,0.9964069,0.00003631424,0.00001096235,0.00001958138,0.00008299018,0.0008847703,0.0003614574],"genre_scores_gemma":[0.08644304,0.0006062295,0.9097595,0.00005672749,0.0000350694,0.0001362831,0.000815433,0.0006081862,0.001539601],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002375462,"threshold_uncertainty_score":0.00794667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704886714608085,"score_gpt":0.2666759077269421,"score_spread":0.2496270405808613,"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."}}