Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Dynamic residual Kaczmarz method for noise reducing reconstruction in magnetic particle imaging | |
Zhang, Peng1; Liu, Jie1![]() ![]() ![]() | |
发表期刊 | PHYSICS IN MEDICINE AND BIOLOGY
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ISSN | 0031-9155 |
2023-07-21 | |
卷号 | 68期号:14页码:17 |
通讯作者 | Liu, Jie(jieliu@bjtu.edu.cn) ; Hui, Hui(hui.hui@ia.ac.cn) |
摘要 | Objective. Here, we propose a dynamic residual Kaczmarz (DRK) method as an improved reconstruction method for magnetic particle imaging (MPI) to achieve a better reconstruction quality from high-noise signals. Approach. Based on the Kaczmarz (KZ) method, we introduced a residual vector to select parts of the low-noise equations for reconstruction. In each iteration, a low-noise subset was formulated based on the residual vector. Thus, the reconstruction converged to an accurate result with less noise. Main Results. To evaluate the performance of the proposed method, it was compared with classical Kaczmarz-type methods and state-of-the-art regularization models. The numerical simulation results demonstrate that the DRK method can achieve better reconstruction quality than all other comparison methods at similar noise levels. It can acquire a signal-to-background ratio (SBR) that is five times higher than that of classical Kaczmarz-type methods at a 5 dB noise level. Furthermore, the DRK method can acquire up to 0.7 structural similarity (SSIM) indicators at a 5 dB noise level when combined with the non-negative fused Least absolute shrinkage and selection operator (LASSO) regularization model. In addition, a real experiment based on the OpenMPI data set validated that the proposed DRK method can be applied to real data and perform well. Significance. The experimental results demonstrate that the proposed DRK method can significantly improve the reconstruction quality of MPI when the signals contain high noise. It has the potential to be applied to MPI instruments that contain high signal noise, such as human-sized MPI instruments. It is beneficial for expanding the biomedical applications of MPI technology. |
关键词 | magnetic particle imaging reconstruction method inverse problem |
DOI | 10.1088/1361-6560/ace022 |
关键词[WOS] | RESOLUTION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2017YFA0700401] ; National Key Research and Development Program of China[2017YFA0700403] ; National Natural Science Foundation of China[62027901] ; National Natural Science Foundation of China[81827808] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81571836] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[KKA309004533] ; Beijing Natural Science Foundation[JQ22023] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences[2018167] ; Chinese Academy of Sciences Key Technology Talent Program ; Project of High-Level Talents Team Introduction in Zhuhai City[HLHPTP201703] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Youth Innovation Promotion Association of the Chinese Academy of Sciences ; Chinese Academy of Sciences Key Technology Talent Program ; Project of High-Level Talents Team Introduction in Zhuhai City |
WOS研究方向 | Engineering ; Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:001025383600001 |
出版者 | IOP Publishing Ltd |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/53688 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Liu, Jie; Hui, Hui |
作者单位 | 1.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China 2.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Engn Med, Beijing 100191, Peoples R China 3.Beihang Univ, Sch Engn Med, Beijing 100191, Peoples R China 4.Beihang Univ, Sch Biol Sci & Med Engn, Beijing 100191, Peoples R China 5.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China 6.Univ Chinese Acad Sci, Beijing 100080, Peoples R China 7.Beihang Univ, Sch Instrumentat & Optoelect Engn, Beijing 100191, Peoples R China |
通讯作者单位 | 中国科学院分子影像重点实验室 |
推荐引用方式 GB/T 7714 | Zhang, Peng,Liu, Jie,Li, Yimeng,et al. Dynamic residual Kaczmarz method for noise reducing reconstruction in magnetic particle imaging[J]. PHYSICS IN MEDICINE AND BIOLOGY,2023,68(14):17. |
APA | Zhang, Peng.,Liu, Jie.,Li, Yimeng.,Zhu, Tao.,Yin, Lin.,...&Tian, Jie.(2023).Dynamic residual Kaczmarz method for noise reducing reconstruction in magnetic particle imaging.PHYSICS IN MEDICINE AND BIOLOGY,68(14),17. |
MLA | Zhang, Peng,et al."Dynamic residual Kaczmarz method for noise reducing reconstruction in magnetic particle imaging".PHYSICS IN MEDICINE AND BIOLOGY 68.14(2023):17. |
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