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Found 2 papers, 1 papers with code
$μ$GUIDE: a framework for microstructure imaging via generalized uncertainty-driven inference using deep learning
The obtained posterior distributions allow to highlight degeneracies present in the model definition and quantify the uncertainty and ambiguity of the estimated parameters.
Inverting brain grey matter models with likelihood-free inference: a tool for trustable cytoarchitecture measurements
Solving the problem of relating the dMRI signal with cytoarchitectural characteristics calls for the definition of a mathematical model that describes brain tissue via a handful of physiologically-relevant parameters and an algorithm for inverting the model.
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