Abstract #2814

Compressed Sensing Using Dual-Tree Complex Wavelet Transform

Yookyung Kim¹, Maria I. Altbach², Theodore P. Trouard^2,3, Ali Bilgin^1,2

¹Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA; ²Radiology, University of Arizona, Tucson, AZ, USA; ³Biomedical Engineering, University of Arizona, Tucson, AZ, USA

Compressed Sensing (CS) holds great promise in accelerating magnetic resonance imaging (MRI). In this work, we explore the use of dual-tree complex wavelet transform (DT-CWT) as a sparsifying transform in CS MRI. Our results indicate that DT-CWT can alleviate some of the shortcomings of traditional discrete wavelet transform.