MODEL BASED IMAGE RECONSTRUCTION USING DEEP LEARNED PRIORS (MODL).
MODL
We introduce a model-based image reconstruction framework, where we use a deep convolution neural network (CNN) based regularization prior.  We rely on a recursive algorithm, which alternates between a CNN based denoising step and enforcement of data consistency.  The unique aspect of this method is the use of the same CNN weights at each iteration, which makes the resulting structure consistent with the model-based formulation. 
CNN
MODEL BASED IMAGE RECONSTRUCTION USING DEEP LEARNED PRIORS (MODL).
MODL