Recent developments of the reconstruction in magnetic particle imaging

被引：43

作者：

Yin, Lin ^{[1
,2
,3
]}

Li, Wei ^{[4
]}

Du, Yang ^{[1
,2
,3
]}

Wang, Kun ^{[1
,2
,3
]}

Liu, Zhenyu ^{[1
,2
,3
]}

Hui, Hui ^{[1
,2
,3
]}

Tian, Jie ^{[1
,2
,3
,5
]}

机构：

[1] Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China

[2] Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China

[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[4] Jinan Univ, Affiliated Hosp 1, Med Imaging Ctr, Guangzhou 510632, Guangdong, Peoples R China

[5] Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing 100083, Peoples R China

来源：

VISUAL COMPUTING FOR INDUSTRY BIOMEDICINE AND ART | 2022年 / 5卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Magnetic particle imaging; Image reconstruction; System matrix; X-space; NANOPARTICLES; FORMULATION; RELAXATION;

D O I：

10.1186/s42492-022-00120-5

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Magnetic particle imaging (MPI) is an emerging molecular imaging technique with high sensitivity and temporal-spatial resolution. Image reconstruction is an important research topic in MPI, which converts an induced voltage signal into the image of superparamagnetic iron oxide particles concentration distribution. MPI reconstruction primarily involves system matrix- and x-space-based methods. In this review, we provide a detailed overview of the research status and future research trends of these two methods. In addition, we review the application of deep learning methods in MPI reconstruction and the current open sources of MPI. Finally, research opinions on MPI reconstruction are presented. We hope this review promotes the use of MPI in clinical applications.

引用

页数：13

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