Smooth Phase Constrained Low-Rank Reconstruction Of High-Resolution Magnetic Resonance Diffusion-Weighted Image

Magnetic Resonance Imaging(MRI)is a non-radioactive medical imaging method that exploits the principle of nuclear magnetic resonance.Usually,the MRI takes a long time,and the parallel imaging method dramatically improves the imaging speed.Diffusion-Weighted Imaging(DWI)is a unique imaging method for non-destructive detection of the diffusion of free water molecules in human body in magnetic resonance imaging.It is widely used in tumor diagnosis,stroke evaluation,and neuroscience research.At present,the most commonly used diffusion-weighted imaging method in the clinic is single-shot Echo-Plane Imaging(ss-EPI).However,single-shot echoplanar imaging is prone to image distortion and has limited imaging resolution.Multishot Echo-Planar Imaging(ms-EPI)resists image distortion and improves image resolution.However,the multi-shot diffusion-weighted imaging method also results in phase variations in the images acquired at different shots,making the collected data unable to be directly synthesized into a high-quality image.How to reconstruct multishot images is an urgent problem.This thesis first proposes a navigator-free reconstruction method based on the structured low-rank matrix derived from the smooth phase property of multi-shot diffusion-weighted images.A structured matrix is constructed using the smooth phase property of the magnetic resonance image.The structured matrices composed of different shot images are then concatenated into a large matrix.The diffusion-weighted image is reconstructed by minimizing the nuclear norm of the concatenated matrix.According to the uniform undersampling characteristic of multi-shot imaging,we combine the nuclear norm constraint with the sensitivity encoding(SENSE)scheme in parallel imaging reconstruction as data consistency to improve the quality of the reconstructed image.Then,we use the partial sum minimization of singular values to further encourage the matrix low-rankness.Simulation data and in vivo brain data experiments show that the proposed method is able to reconstruct high-quality multishot diffusion-weighted images with fewer artifacts and sharper images structure than the state-of-the-art navigator-free reconstruction methods.Furthermore,the improvements in the quality of reconstructed image under high number of shots are more obvious.