{"id":"W2105365961","doi":"10.1109/icdsp.1997.628077","title":"Region growing and region merging image segmentation","year":2002,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pixel; Artificial intelligence; Image segmentation; Region growing; Computer science; Segmentation; Computer vision; Homogeneity (statistics); Range segmentation; Pattern recognition (psychology); Grey scale; Scale (ratio); Image texture; Image (mathematics); Geography; Cartography","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":[0.00243187,0.001065772,0.0017794,0.002882665,0.0009319898,0.001932328,0.00263891,0.001925256,0.002601297],"category_scores_gemma":[0.006797139,0.0009626357,0.001790676,0.002649566,0.001282779,0.002571132,0.001589948,0.001285788,0.002292261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008214031,"about_ca_system_score_gemma":0.0008667058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001643199,"about_ca_topic_score_gemma":0.001456399,"domain_scores_codex":[0.9965979,0.0006814973,0.0001998778,0.001056731,0.001282366,0.0001815938],"domain_scores_gemma":[0.9969316,0.001333377,0.000329538,0.0005277273,0.0007870241,0.00009075674],"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":[0.0004983371,0.00009815545,0.0012136,0.001152653,0.0002833802,0.001004924,0.001026088,0.07862767,0.2461407,0.04835862,0.006505225,0.6150907],"study_design_scores_gemma":[0.00006379454,0.0004612418,0.003781854,0.0001253399,0.0002612562,0.0038679,0.0002554855,0.5931586,0.289547,0.03383092,0.07439064,0.0002559261],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004596133,0.0008669085,0.9920013,0.00006307238,0.00004750341,0.0001300456,0.00007474839,0.0009729296,0.001247423],"genre_scores_gemma":[0.03860805,0.0006872715,0.9578477,0.00006216935,0.00007182175,0.0001589556,0.0002030666,0.0003197018,0.002041369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002882665,"threshold_uncertainty_score":0.01286113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02821349338493596,"score_gpt":0.2662285045932061,"score_spread":0.2380150112082702,"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."}}