An Efficient Compressed Sensing Reconstruction Robust to Phase Variation on MR Images

Satoshi Ito¹, Kazuki Nakamura¹, Yoshifumi Yamada¹

We present a new Compressed Sensing reconstruction that is robust to phase variations in MR images. When the signal trajectory in k-space is symmetrical with respect to its origin, the k-space signal corresponding to the real and imaginary parts of the complex image can be synthesized independently by restricting the k-space signal to an even function or an odd function. The proposed method involves random but symmetrical k-space acquisition and independent reconstruction of the real and imaginary parts of images using the real-valued constraint.