Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method

doi:10.1088/1674-1056/27/8/088701

中国物理B ›› 2018, Vol. 27 ›› Issue (8): 88701-088701.doi: 10.1088/1674-1056/27/8/088701

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇下一篇

Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method

Lin Chen(陈琳), Zhi-Wei Zheng(郑志伟), Li-Jun Bao(包立君), Jin-Sheng Fang(方金生), Tian-He Yang(杨天和), Shu-Hui Cai(蔡淑惠), Cong-Bo Cai(蔡聪波)

1 Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China;
2 Magnetic Resonance Center, Zhongshan Hospital, Medical College of Xiamen University, Xiamen 361004, China;
3 Department of Communication Engineering, Xiamen University, Xiamen 361005, China

收稿日期:2017-11-23 修回日期:2018-04-27 出版日期:2018-08-05 发布日期:2018-08-05
通讯作者: Shu-Hui Cai, Cong-Bo Cai E-mail:shcai@xmu.edu.cn;cbcai@xmu.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 11474236, 81671674, and 11775184) and the Science and Technology Project of Fujian Province, China (Grant No. 2016Y0078).

Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method

Lin Chen(陈琳)¹, Zhi-Wei Zheng(郑志伟)¹, Li-Jun Bao(包立君)¹, Jin-Sheng Fang(方金生)¹, Tian-He Yang(杨天和)², Shu-Hui Cai(蔡淑惠)¹, Cong-Bo Cai(蔡聪波)³

1 Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China;
2 Magnetic Resonance Center, Zhongshan Hospital, Medical College of Xiamen University, Xiamen 361004, China;
3 Department of Communication Engineering, Xiamen University, Xiamen 361005, China

Received:2017-11-23 Revised:2018-04-27 Online:2018-08-05 Published:2018-08-05
Contact: Shu-Hui Cai, Cong-Bo Cai E-mail:shcai@xmu.edu.cn;cbcai@xmu.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 11474236, 81671674, and 11775184) and the Science and Technology Project of Fujian Province, China (Grant No. 2016Y0078).

摘要/Abstract

摘要： An ill-posed inverse problem in quantitative susceptibility mapping (QSM) is usually solved using a regularization and optimization solver, which is time consuming considering the three-dimensional volume data. However, in clinical diagnosis, it is necessary to reconstruct a susceptibility map efficiently with an appropriate method. Here, a modified QSM reconstruction method called weighted total variation using split Bregman (WTVSB) is proposed. It reconstructs the susceptibility map with fast computational speed and effective artifact suppression by incorporating noise-suppressed data weighting with split Bregman iteration. The noise-suppressed data weighting is determined using the Laplacian of the calculated local field, which can prevent the noise and errors in field maps from spreading into the susceptibility inversion. The split Bregman iteration accelerates the solution of the L₁-regularized reconstruction model by utilizing a preconditioned conjugate gradient solver. In an experiment, the proposed reconstruction method is compared with truncated k-space division (TKD), morphology enabled dipole inversion (MEDI), total variation using the split Bregman (TVSB) method for numerical simulation, phantom and in vivo human brain data evaluated by root mean square error and mean structure similarity. Experimental results demonstrate that our proposed method can achieve better balance between accuracy and efficiency of QSM reconstruction than conventional methods, and thus facilitating clinical applications of QSM.

关键词: quantitative susceptibility mapping, ill-posed inverse problem, noise-suppressed data weighting, split Bregman iteration

Abstract: An ill-posed inverse problem in quantitative susceptibility mapping (QSM) is usually solved using a regularization and optimization solver, which is time consuming considering the three-dimensional volume data. However, in clinical diagnosis, it is necessary to reconstruct a susceptibility map efficiently with an appropriate method. Here, a modified QSM reconstruction method called weighted total variation using split Bregman (WTVSB) is proposed. It reconstructs the susceptibility map with fast computational speed and effective artifact suppression by incorporating noise-suppressed data weighting with split Bregman iteration. The noise-suppressed data weighting is determined using the Laplacian of the calculated local field, which can prevent the noise and errors in field maps from spreading into the susceptibility inversion. The split Bregman iteration accelerates the solution of the L₁-regularized reconstruction model by utilizing a preconditioned conjugate gradient solver. In an experiment, the proposed reconstruction method is compared with truncated k-space division (TKD), morphology enabled dipole inversion (MEDI), total variation using the split Bregman (TVSB) method for numerical simulation, phantom and in vivo human brain data evaluated by root mean square error and mean structure similarity. Experimental results demonstrate that our proposed method can achieve better balance between accuracy and efficiency of QSM reconstruction than conventional methods, and thus facilitating clinical applications of QSM.

Key words: quantitative susceptibility mapping, ill-posed inverse problem, noise-suppressed data weighting, split Bregman iteration

中图分类号: (MRI: anatomic, functional, spectral, diffusion)

87.19.lf

33.15.Kr (Electric and magnetic moments (and derivatives), polarizability, and magnetic susceptibility) 02.30.Zz (Inverse problems)

陈琳, 郑志伟, 包立君, 方金生, 杨天和, 蔡淑惠, 蔡聪波. Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method[J]. 中国物理B, 2018, 27(8): 88701-088701.

Lin Chen(陈琳), Zhi-Wei Zheng(郑志伟), Li-Jun Bao(包立君), Jin-Sheng Fang(方金生), Tian-He Yang(杨天和), Shu-Hui Cai(蔡淑惠), Cong-Bo Cai(蔡聪波). Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method[J]. Chin. Phys. B, 2018, 27(8): 88701-088701.

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Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method

Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method

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