{"id":"W2052915721","doi":"10.1117/12.811029","title":"3D variational brain tumor segmentation on a clustered feature set","year":2009,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Segmentation; Artificial intelligence; Pattern recognition (psychology); Voxel; Feature (linguistics); Image segmentation; Boundary (topology); Computer vision; Level set (data structures); 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":[0.001300421,0.0007977236,0.001357386,0.00153815,0.0005536613,0.001203402,0.002015103,0.002012481,0.00113237],"category_scores_gemma":[0.003062301,0.001403198,0.001892297,0.001118844,0.001410215,0.0009780024,0.001355035,0.001049673,0.0003340237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002549349,"about_ca_system_score_gemma":0.001603765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01407591,"about_ca_topic_score_gemma":0.0127508,"domain_scores_codex":[0.9995466,0.00012272,0.00002398175,0.0001374226,0.000117668,0.00005160521],"domain_scores_gemma":[0.9991338,0.0004298968,0.0001056941,0.000101576,0.0001713701,0.00005780226],"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":[0.00008277114,0.00002301195,0.0005448258,0.00004483675,0.00005132109,0.00007197683,0.000076826,0.9577196,0.005075224,0.007961576,0.0007521639,0.02759593],"study_design_scores_gemma":[0.000003644412,0.000005240207,0.0000793229,0.000002587229,0.000002205133,0.00001339383,0.000002963757,0.9970789,0.0004338471,0.002248166,0.0001256297,0.000004141211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02091606,0.00009125147,0.9778602,0.0001334584,0.00001206335,0.00004181424,0.00009463726,0.0004187875,0.0004316673],"genre_scores_gemma":[0.4244714,0.0002045968,0.5706177,0.00020197,0.00005858253,0.0002339233,0.0007462288,0.0005270882,0.002938444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01407591,"threshold_uncertainty_score":0.02798796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01154417308420023,"score_gpt":0.2555251412051694,"score_spread":0.2439809681209691,"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."}}