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… Click to show full abstract
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.
Keywords:
high frequency;
space kernel;
space;
null space;
deep learning
Journal Title: Magnetic Resonance in Medicine
Year Published: 2022
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Journal Title: Magnetic Resonance in Medicine
Year Published: 2022
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!