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Improved l1-SPIRiT using 3D walsh transform-based sparsity basis

By Zhen Feng, Feng Liu, Mingfeng Jiang, Stuart Crozier, He Guo and Yuxin Wang

Abstract

l1-SPIRiT is a fast magnetic resonance imaging (MRI) method which combines parallel imaging (PI) with compressed sensing (CS) by performing a joint l1-norm and l2-norm optimization procedure. The original l1-SPIRiT method uses two-dimensional (2D) Wavelet transform to exploit the intra-coil data redundancies and a joint sparsity model to exploit the inter-coil data redundancies. In this work, we propose to stack all the coil images into a three-dimensional (3D) matrix, and then a novel 3D Walsh transform-based sparsity basis is applied to simultaneously reduce the intra-coil and inter-coil data redundancies. Both the 2D Wavelet transform-based and the proposed 3D Walsh transform-based sparsity bases were investigated in the l1-SPIRiT method. The experimental results show that the proposed 3D Walsh transform-based l1-SPIRiT method outperformed the original l1-SPIRiT in terms of image quality and computational efficiency

Topics: MRI, Compressed Sensing, L1-SPIRiT, Walsh transform, 1304 Biophysics, 2204 Biomedical Engineering, 2741 Radiology Nuclear Medicine and imaging
Publisher: Elsevier
Year: 2014
OAI identifier: oai:espace.library.uq.edu.au:UQ:335608

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