Fast iterative contourlet thresholding for compressed sensing MRI

Wangli Hao; Jianwu Li; Xiaobo Qu; Zhengchao Dong

doi:10.1049/el.2013.1483

Fast iterative contourlet thresholding for compressed sensing MRI

Wangli Hao, Jianwu Li, Xiaobo Qu, Zhengchao Dong

School of Computer Science and Technology

Research output: Contribution to journal › Article › peer-review

24 Citations (Scopus)

Abstract

Proposed is the use of the contourlet as a sparse transform which is combined with the fast iterative shrinkage/threshold algorithm (FISTA) for compressed sensing magnetic resonance imaging reconstruction. The proposed method not only inherits the simplicity and effectiveness of the original FISTA but also has the sparse curve representation ability of the contourlet. Simulation results validate the superior performance of the proposed method in terms of reconstruction accuracy and computation time.

Original language	English
Pages (from-to)	1206-1208
Number of pages	3
Journal	Electronics Letters
Volume	49
Issue number	19
DOIs	https://doi.org/10.1049/el.2013.1483
Publication status	Published - 12 Sept 2013

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10.1049/el.2013.1483

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title = "Fast iterative contourlet thresholding for compressed sensing MRI",

abstract = "Proposed is the use of the contourlet as a sparse transform which is combined with the fast iterative shrinkage/threshold algorithm (FISTA) for compressed sensing magnetic resonance imaging reconstruction. The proposed method not only inherits the simplicity and effectiveness of the original FISTA but also has the sparse curve representation ability of the contourlet. Simulation results validate the superior performance of the proposed method in terms of reconstruction accuracy and computation time.",

author = "Wangli Hao and Jianwu Li and Xiaobo Qu and Zhengchao Dong",

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AU - Hao, Wangli

AU - Li, Jianwu

AU - Qu, Xiaobo

AU - Dong, Zhengchao

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N2 - Proposed is the use of the contourlet as a sparse transform which is combined with the fast iterative shrinkage/threshold algorithm (FISTA) for compressed sensing magnetic resonance imaging reconstruction. The proposed method not only inherits the simplicity and effectiveness of the original FISTA but also has the sparse curve representation ability of the contourlet. Simulation results validate the superior performance of the proposed method in terms of reconstruction accuracy and computation time.

AB - Proposed is the use of the contourlet as a sparse transform which is combined with the fast iterative shrinkage/threshold algorithm (FISTA) for compressed sensing magnetic resonance imaging reconstruction. The proposed method not only inherits the simplicity and effectiveness of the original FISTA but also has the sparse curve representation ability of the contourlet. Simulation results validate the superior performance of the proposed method in terms of reconstruction accuracy and computation time.

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JO - Electronics Letters

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Fast iterative contourlet thresholding for compressed sensing MRI

Abstract

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