{"id":"W1530802675","doi":"10.1109/icip.2004.1418813","title":"Approximation of images by basis functions for multiple region segmentation with level sets","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Basis (linear algebra); Artificial intelligence; Image segmentation; Segmentation; Computer science; Basis function; Pattern recognition (psychology); Computer vision; Scale-space segmentation; Mathematics; Algorithm; Geometry; Mathematical analysis","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":[0.001372073,0.0005037294,0.0009313054,0.001167295,0.0004192009,0.001342503,0.001072026,0.001286193,0.001458299],"category_scores_gemma":[0.003849182,0.0006312061,0.0009125911,0.001154296,0.001063148,0.00161803,0.001114182,0.001628099,0.0006597334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150886,"about_ca_system_score_gemma":0.001013348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001506002,"about_ca_topic_score_gemma":0.001705002,"domain_scores_codex":[0.9993463,0.0001944546,0.00003179405,0.00007003746,0.0003279515,0.00002942354],"domain_scores_gemma":[0.9992332,0.0004266367,0.00006332834,0.0001424358,0.0001053969,0.00002893891],"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":[0.00006823638,0.00004878113,0.0004293716,0.0001727265,0.00005120181,0.0001075634,0.0001831019,0.6061585,0.03292642,0.1893028,0.001651537,0.1688997],"study_design_scores_gemma":[0.000003575671,0.00001228115,0.00006332253,0.000009404355,0.000005015541,0.00003498256,0.000007652675,0.9729056,0.003378195,0.02203155,0.001541675,0.000006867368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001900275,0.000077394,0.9975607,0.00006630638,0.000005620353,0.0000106035,0.000007590542,0.000111006,0.0002604411],"genre_scores_gemma":[0.09157067,0.0004157985,0.9065941,0.00004765819,0.0000166922,0.0001277673,0.00007784243,0.0001772065,0.0009723615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001506002,"threshold_uncertainty_score":0.008350313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03657504727280741,"score_gpt":0.2846522756258054,"score_spread":0.248077228352998,"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."}}