{"id":"W2151059949","doi":"10.1109/ccece.2011.6030435","title":"A novel Accelerated Greedy Snake Algorithm for active contours","year":2011,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Convergence (economics); Algorithm; Greedy algorithm; Computer science; Pixel; Similarity (geometry); Object (grammar); Relaxation (psychology); Artificial intelligence; Mathematical optimization; Image (mathematics); Mathematics","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":[0.0006852921,0.0007948319,0.000941752,0.001060408,0.0004549075,0.0008057883,0.001618672,0.001358265,0.002166419],"category_scores_gemma":[0.001089791,0.0005887126,0.001006168,0.001112361,0.0005777304,0.001273154,0.001055962,0.001163772,0.001207541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003341668,"about_ca_system_score_gemma":0.0007958289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007555766,"about_ca_topic_score_gemma":0.000914547,"domain_scores_codex":[0.9994677,0.00009510192,0.00002394174,0.00009084924,0.0002896773,0.00003278717],"domain_scores_gemma":[0.999685,0.0001136581,0.00003001389,0.00003909662,0.0001061271,0.00002595413],"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":[0.0001717975,0.00009144165,0.0007142312,0.00040549,0.000143872,0.0003952429,0.0001955363,0.1835806,0.06714235,0.0557361,0.01092735,0.6804959],"study_design_scores_gemma":[0.00004639316,0.00008595677,0.0002048038,0.00002748612,0.00003253218,0.0005735799,0.00001777588,0.9402393,0.01064759,0.01436102,0.03372032,0.00004323571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009999707,0.0002060882,0.9978427,0.00005077435,0.00004833702,0.00002109531,0.000009901126,0.000322452,0.0004987764],"genre_scores_gemma":[0.03091806,0.0004215247,0.9659841,0.0001091157,0.00006779844,0.0001191035,0.0001039715,0.0001868846,0.002089421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002166419,"threshold_uncertainty_score":0.007247388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1028411752089919,"score_gpt":0.3178101030545348,"score_spread":0.2149689278455429,"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."}}