Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151068
Title: An efficient Peaceman–Rachford splitting method for constrained TGV-shearlet-based MRI reconstruction
Authors: Wu, Tingting
Zhang, Wenxing
Wang, David Zhi Wei
Sun, Yuehong
Keywords: Engineering::Civil engineering
Issue Date: 2019
Source: Wu, T., Zhang, W., Wang, D. Z. W. & Sun, Y. (2019). An efficient Peaceman–Rachford splitting method for constrained TGV-shearlet-based MRI reconstruction. Inverse Problems in Science and Engineering, 27(1), 115-133. https://dx.doi.org/10.1080/17415977.2018.1451525
Journal: Inverse Problems in Science and Engineering
Abstract: As a fundamental application of compressive sensing, magnetic resonance imaging (MRI) can be efficiently achievable by exploiting fewer k-space measurements. In this paper, we propose a constrained total generalized variation and shearlet transform-based model for MRI reconstruction, which is usually more undemanding and practical to identify appropriate tradeoffs than its unconstrained counterpart. The proposed model can be facilely and efficiently solved by the strictly contractive Peaceman–Rachford splitting method, which generally outperforms some state-of-the-art algorithms when solving separable convex programming. Numerical simulations demonstrate that the sharp edges and grainy details in magnetic resonance images can be well reconstructed from the under-sampling data.
URI: https://hdl.handle.net/10356/151068
ISSN: 1741-5977
DOI: 10.1080/17415977.2018.1451525
Rights: © 2018 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:CEE Journal Articles

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