DEEP LEARNING BASED ACCELERATION FOR ITERATIVE TOMOGRAPHIC RECONSTRUCTION

摘要

The present discussion relates to the use of deep learning techniques to accelerate iterative reconstruction of images, such as CT, PET, and MR images. The present approach utilizes deep learning techniques so as to provide a better initialization to one or more steps of the numerical iterative reconstruction algorithm by learning a trajectory of convergence from estimates at different convergence status so that it can reach the maximum or minimum of a cost function faster.