MoDL: Model-Based Deep Learning Architecture for Inverse Problems
MoDL: Model-Based Deep Learning Architecture for Inverse Problems
We introduce a model-based image reconstruction framework with a convolution neural network (CNN)-based regularization prior. The proposed formulation provides a systematic approach for deriving deep architectures for inverse problems with the arbitrary structure. Since the forward model is explicitly accounted for, a smaller network with fewer parameters is sufficient to …