Yuqiong Ding1, 2, Yiu-Cho Chung1, 2, Leslie Ying3, Dong Liang1, 2
1Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Shenzhen, Guangdong, China; 2Key Laboratory of Health Informatics, Chinese Academy of Sciences, Shenzhen, Guangdong, China; 3Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
As an emerging reconstruction technique, compressed sensing (CS) has demonstrated great potential to reconstruct high quality images from undersampled k-space data. However, the noise behavior of CS reconstruction in MRI remains largely unexplored. This work analyzes how noise is distributed and changed with increasing accelerations. We particularly focus on dynamic contrast-enhanced imaging (DCE-MRI), where the temporal and spatial noise behavior in CS-based DCE-MRI is characterized using the Marcenko-Pastur (MP)-Law method. The study provides a qualitative understand of the noise behavior in CS reconstructed DCE images. Such understanding can accelerate application of CS in clinical practice.