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Convergent ADMM Plug and Play PET Image Reconstruction
In this work, we investigate hybrid PET reconstruction algorithms based on coupling a model-based variational reconstruction and the application of a separately learnt Deep Neural Network operator (DNN) in an ADMM Plug and Play framework.
Deep Unfolding of the DBFB Algorithm with Application to ROI CT Imaging with Limited Angular Density
We unfold the Dual Block coordinate Forward-Backward (DBFB) algorithm, embedded in an iterative reweighted scheme, allowing the learning of key parameters in a supervised manner.
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