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A Comprehensive Framework for Uncertainty Quantification of Voxel-wise Supervised Models in IVIM MRI

A probabilistic deep learning framework based on Deep Ensembles of Mixture Density Networks of MDNs of IVIM parameters is proposed, enabling estimation of total predictive uncertainty and decomposition into aleatoric (AU) and epistemic (EU) components.
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Physics-Informed CNN Ensemble for Improved Tissue Perfusion and Diffusion Estimation with Uncertainty Quantification in IVIM MRI

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