DYNAMIC MRI RECONSTRUCTION USING LOW RANK PLUS SPARSE TENSOR DECOMPOSITION

被引：0

作者：

Roohi, Shahrooz Faghih ^{[1
]}

Zonoobi, Domoosh ^{[2
]}

Kassim, Ashraf A. ^{[1
]}

Jaremko, Jacob L. ^{[2
]}

机构：

[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore, Singapore

[2] Univ Alberta Hosp, Dept Radiol & Diagnost Imaging, Edmonton, AB T6G 2B7, Canada

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2016年

关键词：

Low-Rank and Sparse Tensor Decomposition; Dynamic 3D MRI; Image Reconstruction; Compressive sensing; SEQUENCES; SIGNALS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we introduce a multi-dimensional approach to the problem of reconstruction of MR image sequences that are highly undersampled in k-space. By formulating the reconstruction as a high-order low-rank plus sparse tensor decomposition problem, we propose an efficient numerical algorithm based on the alternating direction method of multipliers (ADMM) to solve the optimization. Through extensive experimental results we show that our proposed method achieves superior reconstruction quality, compared to the state-of-the-art reconstruction methods.

引用

页码：1769 / 1773

页数：5

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