The Multiple Transforms Compressed Sensing for MR Angiography

Joonsung Choi¹, Yeji Han¹, Jinyoung Hwang¹, Jun-Young Chung², Zang-Hee Cho², HyunWook Park¹

Compressed sensing (CS) is a newly emerging technique to reconstruct undersampled signal. If certain conditions, such as sparsity and incoherent sampling, are satisfied, the signal can be accurately reconstructed from undersampled data by the CS technique. Therefore, a sparsifying transform is required in the CS technique for the target signal. Conventionally, the CS uses a single sparsifying transform. However, the target signal can be more sparsely represented in some cases by adopting multiple sparsifying transforms. In this work, an adaptive CS algorithm using two transforms is proposed to reconstruct MR angiography images with high accuracy and quality.