A Comparative Study of Compressed Sensing Approaches with Splitting Bregman Framework for Radial UTE MRI

作者：Bi Dong Jie; Le Xie Yong; Ma Lan; Xie Xuan; Niu Pan

来源：2015 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD), 2015, 39-41.

DOI：10.1109/asemd.2015.7453456

• MRI
• UTE
• radial
• compressed sensing
• NUFFT

This paper investigates two compressed sensing (CS) approaches that can be used to reconstruct radial Magnetic Resonance (MR) images with undersampled k-space measurements. Combining CS with gridding and non-uniform fast Fourier transform (NUFFT), yields two different approaches: Regridding-CS and NUFFT-CS. Under splitting Bregman framework, these approaches can decrease the load of data acquisition while recovering MR images through l(1)-norm and total variation (TV) optimization. Experiments using a phantom example have verified that the NUFFT-CS achieves better image quality than the Regridding-CS.

• 出版日期2015
• 单位电子科技大学