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Found 4 papers, 3 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.
Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine Learning
In this paper, we demonstrate self-supervised machine learning model fitting for a directional microstructural model.
Lossy compression of multidimensional medical images using sinusoidal activation networks: an evaluation study
In this work, we evaluate how neural networks with periodic activation functions can be leveraged to reliably compress large multidimensional medical image datasets, with proof-of-concept application to 4D diffusion-weighted MRI (dMRI).
Multi-Stage Prediction Networks for Data Harmonization
Specifically, we introduce the Multi Stage Prediction (MSP) Network, a MTL framework that incorporates neural networks of potentially disparate architectures, trained for different individual acquisition platforms, into a larger architecture that is refined in unison.
