{"id":"W2130748174","doi":"10.1109/nfsi-icfbi.2007.4387709","title":"Medical Image Segmentation: Methods and Software","year":2007,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Segmentation; Image segmentation; Scale-space segmentation; Segmentation-based object categorization; Computer science; Artificial intelligence; Region growing; Process (computing); Software; Computer vision; Minimum spanning tree-based segmentation; Pattern recognition (psychology)","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":[0.003031924,0.001189794,0.001564416,0.00443249,0.0007695631,0.003436685,0.002434517,0.0025849,0.01033319],"category_scores_gemma":[0.006702117,0.001241534,0.001059205,0.005057802,0.001743844,0.002870556,0.002348377,0.002050611,0.01462534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008653475,"about_ca_system_score_gemma":0.001349906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00108804,"about_ca_topic_score_gemma":0.0007695224,"domain_scores_codex":[0.9969581,0.0005449784,0.0002755728,0.0004221907,0.001728367,0.00007071877],"domain_scores_gemma":[0.9972134,0.001205568,0.000221537,0.0005256155,0.0007256576,0.0001081513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008218653,0.00006308917,0.000487615,0.002293509,0.0001138163,0.0001825775,0.00030355,0.01551979,0.01252802,0.07228477,0.06433379,0.8318073],"study_design_scores_gemma":[0.00005032784,0.00009257828,0.001731514,0.0009527372,0.0001085311,0.002492673,0.000138372,0.1390807,0.02113319,0.1451415,0.6888744,0.0002034186],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000507489,0.00903558,0.978999,0.000640222,0.0001944086,0.0001610836,0.0003587508,0.0044555,0.005647908],"genre_scores_gemma":[0.01272746,0.01290795,0.9627176,0.000361111,0.0004692391,0.0005065494,0.0009575404,0.001497614,0.007854976],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01033319,"threshold_uncertainty_score":0.03456795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750947217430318,"score_gpt":0.4001116249803628,"score_spread":0.3826021528060596,"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."}}