Introducing µGUIDE for quantitative imaging via generalized uncertainty-driven inference using deep learning

This work proposes µGUIDE: a general Bayesian framework to estimate posterior distributions of tissue microstructure parameters from any given biophysical model or signal representation, with exemplar demonstration in diffusion-weighted magnetic resonance imaging. Harnessing a new deep learning arch...

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Bibliographic Details
Main Authors: Maëliss Jallais, Marco Palombo
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2024-11-01
Series:eLife
Subjects:
Online Access:https://elifesciences.org/articles/101069
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