Compressed sensing MRI by two-dimensional wavelet filter banks

Zangen Zhu, Ran Yang, Jingxin Zhang, Cishen Zhang

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

6 Citations (Scopus)


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).

Original languageEnglish
Title of host publication2011 7th International Workshop on Multidimensional (nD) Systems, nDS 2011
Subtitle of host publicationPoitiers, France; 5-7 September 2011
EditorsO. Bachelier, K. Galkowski, E. Rogers
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781612848174
ISBN (Print)9781612848167, 9781612848150
Publication statusPublished - 2011
EventInternational Workshop on Multidimensional Systems 2011 - Poitiers, France
Duration: 5 Sep 20117 Sep 2011
Conference number: 7th


ConferenceInternational Workshop on Multidimensional Systems 2011
Abbreviated titlenDS 2011

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