Improving high frequency image features of deep learning reconstructions via k-space refinement with null-space kernel.
Journal:
Magnetic resonance in medicine
Published Date:
Apr 15, 2022
Abstract
PURPOSE: Deep learning (DL) based reconstruction using unrolled neural networks has shown great potential in accelerating MRI. However, one of the major drawbacks is the loss of high-frequency details and textures in the output. The purpose of the study is to propose a novel refinement method that uses null-space kernel to refine k-space and improve blurred image details and textures.