{"id":"W4211008077","doi":"10.1364/boe.447394","title":"Convolutional dictionary learning for blind deconvolution of optical coherence tomography images","year":2022,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Los Alamos National Laboratory; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Deconvolution; Optical coherence tomography; Point spread function; Speckle pattern; Speckle noise; Weighting; Brightness; Blind deconvolution; Noise (video); Pattern recognition (psychology)","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":[0.0006884069,0.0004815361,0.0003820342,0.0003359863,0.0002015067,0.0003385493,0.0005751002,0.0006124621,0.0008071339],"category_scores_gemma":[0.00234524,0.0001955835,0.0003417113,0.0004075685,0.000504402,0.0005923059,0.0007247429,0.0007267161,0.0003625852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005323833,"about_ca_system_score_gemma":0.000962462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004271083,"about_ca_topic_score_gemma":0.004318668,"domain_scores_codex":[0.9997336,0.00008150293,0.00001466444,0.00005377267,0.00008401419,0.00003240148],"domain_scores_gemma":[0.9993674,0.0002488572,0.0000767126,0.0001147571,0.0001636854,0.00002862397],"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":[0.0003010631,0.00009498493,0.001083422,0.0001617686,0.0001065733,0.0001051056,0.0001068853,0.5353068,0.06580603,0.03061771,0.004496481,0.3618132],"study_design_scores_gemma":[0.000004616501,0.00001246889,0.00008880594,0.000002553722,0.000003157314,0.00001961918,0.000002762923,0.9927365,0.004127387,0.002357088,0.0006409877,0.000004211975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00898828,0.00008574226,0.9901854,0.00007534979,0.00001346475,0.00001073657,0.00004601759,0.0002063619,0.0003886388],"genre_scores_gemma":[0.3049035,0.0003440542,0.6906016,0.0001558121,0.00004363538,0.00009677639,0.0003617354,0.0001196619,0.003373207],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004271083,"threshold_uncertainty_score":0.00849247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01474155007540289,"score_gpt":0.2478205728831653,"score_spread":0.2330790228077624,"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."}}