International Journal on Magnetic Particle Imaging IJMPI
Vol. 9 No. 1 Suppl 1 (2023): Int J Mag Part Imag

Short Abstracts

A Modular Magnetic Particle Imaging Simulation system for fast reconstruction

Main Article Content

Yusong Shen (School of Computer Science and Engineering, Southeast University, Nanjing, China), Liwen Zhang  (CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China), Guang Jia  (School of Computer Science and Technology, Xidian University, Xi’an Shaanxi, China), Yaxin Shang  (School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China), Jing Zhao  (School of Biological Science and Medical Engineering, Beihang University, Beijing, China), Tan Wang (CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China), Yimeng Li (School of Biological Science and Medical Engineering, Beihang University, Beijing, China), Jie Tian  (School of Computer Science and Engineering, Southeast University, Nanjing, China), Hui Hui  (CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China)

Copyright (c) 2023 Yusong Shen, Liwen Zhang , Guang Jia , Yaxin Shang , Jing Zhao , Tan Wang, Yimeng Li, Jie Tian , Hui Hui

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

How to developa modular simulation system forfast reconstruction of different dimensional MPI images is significant fordesign of MPI system. In this study, we propose a modular and open-source MPI simulation system, which consists of the virtual phantom module, MPI scanner module, particle magnetization module, reconstruction module, and quantitative evaluation module. Combining the MPI scanner module and the particle magnetization module can produce the simulated voltage signal of the superparamagnetic iron oxide (SPIO) magnetization. The system enables the integration of the different MPI reconstruction methods to reconstruct an image from the simulated voltage signal of the SPIO magnetization. The quantitative evaluation module can analyze the MPI system performance by comparing the differences between the simulation reconstruction image and the virtual phantom image. Each module can be easily extended. Now, our simulation system is implemented using Python 3.8 with the open scientific computing libraries Numpy and Scipy and supports the simulation of 1-D, 2-D and 3-D MPI systems and batch simulation tasks. We have shown in this work the early stages of the development of our MPI simulation system which is designed to provide an optimal design solution is selected for the new MPI system. In future, we will improve the system with a focus on adding more features, such as field-free line simulation, non-Langevin particle magnetization and other relaxation modeling, etc. The source code of the simulation system is available on http://mpilab.net/en/simulation/.




Article Details

References

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