{"id":"W2002074584","doi":"10.1080/1025584021000003874","title":"Skeletonization of Volumetric Angiograms for Display","year":2002,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics & Biomedical Engineering","topic":"Digital Image Processing Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Skeletonization; Topological skeleton; Voxel; Curvature; Artificial intelligence; Medial axis; Computer vision; Segmentation; Mathematics; Computer science; Smoothing; Shape analysis (program analysis); Tangent; Geometry; Active shape model","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":[0.0006092617,0.0007889543,0.000562585,0.002473837,0.0003433568,0.001574408,0.000659312,0.0006055344,0.02483177],"category_scores_gemma":[0.003993048,0.0004881546,0.0005595621,0.001376879,0.0003239809,0.0009039397,0.001004897,0.000956181,0.006769193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002736974,"about_ca_system_score_gemma":0.000672136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006380056,"about_ca_topic_score_gemma":0.0008774315,"domain_scores_codex":[0.9997113,0.0000529799,0.00002805702,0.00004272766,0.0001308185,0.00003401988],"domain_scores_gemma":[0.9987584,0.0004339595,0.00007877265,0.0003813069,0.0002820682,0.00006547337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004981765,0.00008623509,0.0007363049,0.0003632806,0.00003962203,0.0005949456,0.0001810066,0.01311172,0.2325734,0.02149452,0.03214402,0.6981768],"study_design_scores_gemma":[0.0001694749,0.0002637161,0.007240438,0.0001678214,0.00006536557,0.003968205,0.0001413017,0.55702,0.2159306,0.04711774,0.1677671,0.0001480986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008511163,0.0001924554,0.9749326,0.0002275408,0.00009664417,0.0001301116,0.0008253098,0.01155583,0.003528339],"genre_scores_gemma":[0.07514611,0.0006953678,0.914281,0.0000980046,0.0001590565,0.0002331274,0.002423058,0.002969438,0.003994887],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02483177,"threshold_uncertainty_score":0.08307058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02584135129234401,"score_gpt":0.3153706224222706,"score_spread":0.2895292711299266,"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."}}