Article

Sparse representation of complex MRI images.

Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX, USA.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2008; 2008:398-401. DOI:10.1109/IEMBS.2008.4649174 pp.398-401
Source: PubMed

ABSTRACT Sparse representation of images acquired from Magnet Resonance Imaging (MRI) has several potential applications. MRI is unique in that the raw images are complex. Complex wavelet transforms (CWT) can be used to produce flexible signal representations when compared to Discrete Wavelet Transform (DWT). In this work, five different schemes using CWT or DWT are tested for sparse representation of MRI images which are in the form of complex values, separate real/imaginary, or separate magnitude/phase. The experimental results on real in-vivo MRI images show that appropriate CWT, e.g., dual-tree CWT (DTCWT), can achieve sparsity better than DWT with similar Mean Square Error.

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Keywords

Complex wavelet
 
Discrete Wavelet Transform
 
DWT
 
experimental results
 
flexible signal representations
 
Magnet Resonance Imaging
 
raw images
 
real in-vivo MRI images
 
separate real/imaginary
 
similar Mean Square Error
 
sparse representation