{"id":"W4404903795","doi":"10.3390/life14121580","title":"Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion Models","year":2024,"lang":"en","type":"article","venue":"Life","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Strong; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Arizona State University; Biogen; Eli Lilly and Company; BioClinica; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Positron emission tomography; Neuroimaging; Partial volume; Leverage (statistics); Statistical power; Pet imaging; Magnetic resonance imaging; Amyloid (mycology); Computer science; Artificial intelligence; Biomedical engineering; Nuclear medicine; Medicine; Pathology; Neuroscience; Radiology; Mathematics; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001374617,0.000696161,0.0004951016,0.0005045427,0.0001631491,0.0007853014,0.0006442417,0.0008565366,0.0005835059],"category_scores_gemma":[0.004627622,0.0003389617,0.0006046322,0.0004096946,0.0004924299,0.00132076,0.0009624216,0.001084869,0.0002451111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004752958,"about_ca_system_score_gemma":0.000651556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001827299,"about_ca_topic_score_gemma":0.002657801,"domain_scores_codex":[0.9997188,0.0001078468,0.0000165964,0.00005901711,0.00007161572,0.00002607255],"domain_scores_gemma":[0.9987825,0.0007394931,0.0001831842,0.000123743,0.0001278732,0.000043179],"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":[0.0003077436,0.0001353467,0.002363333,0.000221999,0.0001237419,0.0002017385,0.0001434034,0.7484615,0.08532161,0.007632922,0.001265168,0.1538215],"study_design_scores_gemma":[0.00000476529,0.00001560047,0.0001474185,0.000004555135,0.000006694255,0.00003921307,0.000002971935,0.9919816,0.005966662,0.001589071,0.0002346331,0.000006949224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03340971,0.0003774019,0.9649631,0.0002549501,0.00001378527,0.0000176678,0.00006220746,0.0005328719,0.0003682526],"genre_scores_gemma":[0.5801609,0.0005810259,0.4173902,0.000245914,0.00003136812,0.00006260901,0.000268845,0.0002081396,0.001050958],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001827299,"threshold_uncertainty_score":0.00726974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1642666231847621,"score_gpt":0.3816011422324775,"score_spread":0.2173345190477154,"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."}}