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Found 3 papers, 1 papers with code
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz
We compare our proposed approach with baseline methods: Monte-Carlo dropout and deep ensembles, and further analysis included MRI denoising and Computed Tomography (CT) sparse-to-full view reconstruction using UNET architectures.
Institutionally Distributed Deep Learning Networks
In such cases, sharing a deep learning model is a more attractive alternative.
Image reconstruction by domain transform manifold learning
Image reconstruction plays a critical role in the implementation of all contemporary imaging modalities across the physical and life sciences including optical, MRI, CT, PET, and radio astronomy.
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