{"id":"W1989681749","doi":"10.1109/tip.2014.2351620","title":"Robust Volumetric Texture Classification of Magnetic Resonance Images of the Brain Using Local Frequency Descriptor","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; ALS Association","keywords":"Artificial intelligence; Voxel; Robustness (evolution); Computer vision; Computer science; Local binary patterns; Pattern recognition (psychology); Texture (cosmology); Image texture; Image processing; Histogram; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004672842,0.0005189714,0.0008232394,0.002909592,0.0002410861,0.0009698735,0.0006088121,0.0004716534,0.001104721],"category_scores_gemma":[0.001859364,0.0001984207,0.0007774649,0.001587398,0.0003592299,0.0009289897,0.0005133462,0.0005757424,0.0006105962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000387125,"about_ca_system_score_gemma":0.0004304059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001931618,"about_ca_topic_score_gemma":0.001604198,"domain_scores_codex":[0.9996052,0.00004290498,0.00002495985,0.00006878209,0.0002021612,0.00005595289],"domain_scores_gemma":[0.999517,0.0001287851,0.00009619979,0.00007569873,0.0001555655,0.00002677739],"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":[0.0002744151,0.00008789749,0.002339012,0.0002517137,0.00008847855,0.0001389939,0.0000859517,0.02387014,0.1417886,0.003638543,0.003940324,0.8234959],"study_design_scores_gemma":[0.00004433651,0.0002005864,0.01335211,0.00004355462,0.0001282316,0.001030261,0.0001824071,0.8894749,0.08069562,0.007438981,0.007304952,0.0001040596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03183678,0.000335993,0.9656762,0.00008232749,0.0000596067,0.00005660007,0.0002026963,0.0008946183,0.0008551039],"genre_scores_gemma":[0.4226697,0.0008549544,0.5722804,0.0001119435,0.0001843245,0.0001663492,0.0014021,0.0002917251,0.002038512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002909592,"threshold_uncertainty_score":0.003840744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02853366812971117,"score_gpt":0.250448830262185,"score_spread":0.2219151621324738,"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."}}