NDLI: Directional tensor product complex tight framelets for compressed sensing MRI reconstruction

Content Provider	IET Digital Library
Author	Jiang, Mingfeng Lu, Liang Shen, Yi Wu, Long Gong, Yinglan Xia, Ling Liu, Feng
Abstract	Compressed sensing magnetic resonance imaging (CS-MRI) is an effective way of reducing the sampling data in the k-space and shortening the scanning time. Motivated by the high performance of directional tensor product complex tight framelets (TPCTFs) for the image denoising problem, the authors proposed a novel framework that integrated TPCTF for sparse representation and projected fast iterative soft-thresholding algorithm (pFISTA) for CS-MRI reconstruction. Furthermore, to take advantage of the cross-scale relations in the wavelet tree of frame coefficients, the bivariate shrinkage (BS) function with local variance estimation is proposed to shrink thresholding. Such TPCTFs can provide sparse directional representations very well for MR image. When compared with other the state-of-the-art CS-MRI algorithms in numerical experiments, the proposed TPCTF-BS method achieves a higher reconstruction quality with respect to image edge preservation and the artefact suppression.
Starting Page	2183
Ending Page	2189
Page Count	7
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 12, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5614
Journal	IET Image Processing
Publisher Date	2019-08-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Artefact Suppression Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Bivariate Shrinkage Function Combinatorial Mathematics Compressed Magnetic Resonance Imaging Compressed Sensing Compressed Sensing MRI Reconstruction Computer Vision And Image Processing Technique Cross-scale Relations CS-MRI Reconstruction Directional Tensor Product Complex Tight Framelets Graph Theory Image Denoising Image Denoising Problem Image Edge Preservation Image Reconstruction Image Representation Integral Transforms in Numerical Analysis Interpolation And Function Approximation Iterative Method Linear Algebra Local Variance Estimation Mathematics Medical Image Processing Medical Magnetic Resonance Imaging And Spectroscopy Numerical Analysis Numerical Approximation And Analysis Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Projected Fast Iterative Soft-thresholding Algorithm Set Theory Shrink Thresholding Soft-thresholding Algorithm Sparse Directional Representations Spectroscopy Tensors Trees Wavelet Transform Wavelet Tree
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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