{"id":"W2783775739","doi":"10.1016/j.media.2018.09.002","title":"Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections","year":2018,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Engineering and Physical Sciences Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; Servier; Eisai; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; BioClinica; National Institute of Mental Health; Neurosciences Research Foundation; National Center for Research Resources; F. Hoffmann-La Roche; University of Southern California; Wellcome Trust; National Institute of Diabetes and Digestive and Kidney Diseases; Synarc; Medpace; European Research Council; Northern California Institute for Research and Education; Massachusetts General Hospital; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Artificial intelligence; Image registration; Computer science; Probabilistic logic; Computer vision; Rigid transformation; Robustness (evolution); Mutual information; Pattern recognition (psychology); Metric (unit); Inference; Affine transformation; Bayesian inference; Real-time MRI; Bayesian probability; Image (mathematics); Magnetic resonance imaging; Mathematics","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":[0.002644643,0.0009574057,0.001164346,0.001421944,0.0004693544,0.001443079,0.002194639,0.001940098,0.002066826],"category_scores_gemma":[0.004840335,0.001566357,0.002563697,0.001093179,0.001569008,0.001304305,0.001758222,0.002040057,0.001084491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128521,"about_ca_system_score_gemma":0.002246815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004481025,"about_ca_topic_score_gemma":0.006729511,"domain_scores_codex":[0.9982995,0.0003465679,0.00009114984,0.0005519472,0.0006290568,0.0000817422],"domain_scores_gemma":[0.9986562,0.0006010412,0.0002675515,0.0002140461,0.0001991989,0.00006210987],"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":[0.00008895389,0.00003826151,0.0004868903,0.0001443206,0.00007373356,0.0001075669,0.0001042516,0.8890337,0.01960864,0.01730474,0.0006833402,0.07232562],"study_design_scores_gemma":[0.00001173991,0.00003618532,0.0002113708,0.00001187835,0.00001751821,0.00008752703,0.000006500119,0.987663,0.00337795,0.007226288,0.001325692,0.00002433314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001168732,0.00005291772,0.9983028,0.0000336472,0.00000833246,0.00001953647,0.00002094984,0.0002292113,0.0001638034],"genre_scores_gemma":[0.1546258,0.0005195394,0.8394512,0.0001682233,0.00009109826,0.00050169,0.0004545204,0.0005099775,0.003678004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004481025,"threshold_uncertainty_score":0.01398635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04816367954821354,"score_gpt":0.3234920483452383,"score_spread":0.2753283687970248,"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."}}