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Uncertainty quantification in medical image synthesis:
Jin, B
;
Barbano, R
;
Arridge, S
.
https://discovery.ucl.ac.uk/id/eprint/10129844/1/BookChapter_Modelling_Uncertainty_General_Latex.pdf. , 2022
Link:
https://discovery.ucl.ac.uk/id/eprint/10129844/1/BookC..
RT Journal T1 <Title>Uncertainty quantification in medical image synthesis</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftucl:oai:eprints.ucl.ac.uk.OAI2:10129844&Exemplar=1&LAN=DE A1 Jin, B A1 Barbano, R A1 Arridge, S A1 Tanno, R PB Elsevier YR 2022 K1 uncertainty quantification K1 medical image synthesis K1 deep learning; approximate inference; Bayesian neural networks JF https://discovery.ucl.ac.uk/id/eprint/10129844/1/BookChapter_Modelling_Uncertainty_General_Latex.pdf LK http://dx.doi.org/https://discovery.ucl.ac.uk/id/eprint/10129844/1/BookChapter_Modelling_Uncertainty_General_Latex.pdf DO https://discovery.ucl.ac.uk/id/eprint/10129844/1/BookChapter_Modelling_Uncertainty_General_Latex.pdf SF ELIB - SuUB Bremen
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