Sehoon Lim1, Dosik Hwang2
1SRI International Sarnoff, Princeton, NJ, United States; 2School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
A set of different contrast MR images are usually necessary for proper diagnosis. However, the multiple acquisitions of several contrast images require long scanning time. In this study, we propose an efficient multimode compressed sensing (CS) framework to reduce the total scanning time by undersampling the k-space data of each contrast (mode) image and reconstructing artifact-minimized images. In contrast to other groups, we used a wavelet based multiscale selection CS technique to alleviate computational burden. In our studies, the running time of the proposed wavelet multimode CS is presented as a minute, which is promising for agile and compact applications.