A unified approach for maintaining MRI reconstruction quality and quantifying both aleatoric and epistemic uncertainty
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This study investigates practical design choices for Bayesian uncertainty quantification (UQ) in model-based deep learning (MoDL) for accelerated MRI reconstruction. Specifically, we examine where to introduce stochastic layers to capture epistemic uncertainty... ...
