Recent developments of the reconstruction in magnetic particle imaging.

4区 计算机科学 Q1 Arts and Humanities Visual Computing for Industry, Biomedicine, and Art Pub Date : 2022-10-01 DOI:10.1186/s42492-022-00120-5
Lin Yin, Wei Li, Yang Du, Kun Wang, Zhenyu Liu, Hui Hui, Jie Tian
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引用次数: 12

Abstract

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.

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磁粒子成像重建的最新进展。
磁颗粒成像(MPI)是一种新兴的高灵敏度、高时空分辨率的分子成像技术。图像重建是MPI中的一个重要研究课题,它将感应电压信号转换成超顺磁性氧化铁颗粒浓度分布的图像。MPI重建主要涉及基于系统矩阵和x空间的方法。在本文中,我们对这两种方法的研究现状和未来的研究趋势进行了详细的概述。此外,我们回顾了深度学习方法在MPI重建中的应用以及当前开放的MPI源代码。最后,提出了MPI重建的研究意见。我们希望这篇综述能促进MPI在临床中的应用。
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来源期刊
Visual Computing for Industry, Biomedicine, and Art
Visual Computing for Industry, Biomedicine, and Art Arts and Humanities-Visual Arts and Performing Arts
CiteScore
5.60
自引率
0.00%
发文量
28
审稿时长
5 weeks
期刊最新文献
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