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Abstract #2814

Compressed Sensing Using Dual-Tree Complex Wavelet Transform

Yookyung Kim1, Maria I. Altbach2, Theodore P. Trouard2,3, Ali Bilgin1,2

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.