{"id":"W2166086209","doi":"10.1364/oe.17.000733","title":"Interval type-II fuzzy anisotropic diffusion algorithm for speckle noise reduction in optical coherence tomography images","year":2009,"lang":"en","type":"article","venue":"Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Speckle noise; Optical coherence tomography; Speckle pattern; Anisotropic diffusion; Algorithm; Optics; Noise (video); Computer science; Noise reduction; Artificial intelligence; Computer vision; Mathematics; Physics; 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":[0.0006817803,0.000353508,0.0004711912,0.0005119269,0.0002633164,0.0004901432,0.0007315117,0.0005560004,0.0007329115],"category_scores_gemma":[0.001466883,0.0001767827,0.0004440611,0.0004288791,0.0002992646,0.000502101,0.000250198,0.0005761986,0.0001810188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004775945,"about_ca_system_score_gemma":0.0005104695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002709451,"about_ca_topic_score_gemma":0.0027335,"domain_scores_codex":[0.9997203,0.00004585353,0.00002226845,0.00004601114,0.0001493824,0.00001624067],"domain_scores_gemma":[0.9996376,0.0001305408,0.00003476901,0.00002316507,0.0001599944,0.00001382326],"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":[0.0002897486,0.00009300912,0.0008929373,0.0001694534,0.00007455177,0.0001242715,0.0001711765,0.2258876,0.07853493,0.01369715,0.001535268,0.6785299],"study_design_scores_gemma":[0.00001546347,0.0000481522,0.0002642921,0.000006337971,0.00001304938,0.00006315113,0.000008846428,0.9887319,0.00828876,0.00147438,0.001072681,0.0000129853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00990464,0.0001081114,0.989337,0.00003550316,0.00001754054,0.00001829873,0.000008219621,0.0001051776,0.0004655086],"genre_scores_gemma":[0.1477864,0.0001471528,0.8507576,0.00004074907,0.00002128722,0.00006361726,0.00003854904,0.00002300578,0.001121633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002709451,"threshold_uncertainty_score":0.005387366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118341947486242,"score_gpt":0.2468543851277884,"score_spread":0.235670965652926,"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."}}