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发布时间：2019-03-09

论文类型：期刊论文

发表时间：2014-09-01

发表刊物：MAGNETIC RESONANCE IMAGING

收录刊物：Scopus、PubMed、SCIE

卷号：32

期号：7

页面范围：924-933

ISSN号：0730-725X

关键字：MRI; Compressed Sensing; l1-SPIRiT; Walsh transform

摘要：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. (C) 2014 Elsevier Inc. All rights reserved.