NDLI: Compressed sensing MRI by two-dimensional wavelet filter banks

Content Provider	IEEE Xplore Digital Library
Author	Zangen Zhu Ran Yang Jingxin Zhang Cishen Zhang
Copyright Year	2011
Description	Author affiliation: Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia (Cishen Zhang) \|\| School of Information Science and Technology, Sun Yat-Sen University, Guangzhou 510275, China (Zangen Zhu; Ran Yang) \|\| Department of Computer Systems and Electrical Engineering, Monash University, Clayton, VIC 3800, Australia (Jingxin Zhang)
Abstract	How to speed up the scanning process is the bottleneck problem of magnetic resonance imaging (MRI). As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS) provides a solution to this problem because of its potential of reconstructing MR images from fewer samples. Recent work has demonstrated successful application of CS to MRI. However, the frequently used sparsifying transform is the traditional discrete wavelet transform, which has shortcomings, such as oscillations, lack of directionality and shift variance. This paper implements compressed sensing MRI reconstruction based on a new kind of two-dimensional wavelet filter banks which has improved directional selectivity and approximate shift invariance. Our experiments show that the method can significantly reduce aliasing and achieve higher peak signal to noise ratio (PSNR).
Starting Page	1
Ending Page	6
File Size	601401
Page Count	6
File Format	PDF
ISBN	9781612848150
e-ISBN	9781612848174
DOI	10.1109/nDS.2011.6076845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-05
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Phantoms Discrete wavelet transforms Image reconstruction Compressed sensing
Content Type	Text
Resource Type	Article

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