Abstract
Objectives
In open structure MPI systems, the nonlinear variation of the field free lines in the large region of interest scanning process distorts the x-space image reconstruction. In this study, we propose a nonlinear field free line projection reconstruction algorithm to solve the edge distortion problem of open structure MPI imaging.
Methods
First, we calculate the curvature change law of the field free line in the scanning process. Then, we design a nonlinear back projection reconstruction algorithm according to the nonlinear characteristics of the field free line in the scanning process. Finally, the nonlinear back projection reconstruction algorithm is used to complete the tomography of blood vessels.
Results
The numerical calculation and simulation results show that the open structure MPI combined with a nonlinear back projection reconstruction algorithm can accomplish vascular fault reconstruction. The reconstruction algorithm proposed in this paper suppresses the edge distortion of the image and improves the positioning accuracy of the image. The size of the region of interest where distortions are low is increased 16 times by allowing 10.9% degradation in the gradient.
Conclusions
We provide a non-linear inverse projection reconstruction algorithm to reduce the structural artefacts caused by FFL distortion. It provides a reconstruction scheme for a large region of interest fine imaging of open structure FFL-MPI.
Funding source: The National Nature Science Foundation of China
Award Identifier / Grant number: 52077143
Funding source: The tackling-key project from Liaoning Education Department
Award Identifier / Grant number: LZGD2020002
Funding source: Liaoning Provincial Education Department Scientific Research Project
Award Identifier / Grant number: LJKZ0131
Acknowledgments
This work is supported by the National Nature Science Foundation of China (52077143), Liaoning Provincial Education Department Scientific Research Project (LJKZ0131) and the tackling-key project from Liaoning Education Department (LZGD2020002).
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Research funding: The National Nature Science Foundation of China (52077143), the Nature Science Foundation of Liaoning Province (2019-ZD-0204) and the tackling-key project from Liaoning Education Department (LZGD2020002).
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Author contributions: All authors have accepted respon-sibility for the entire content of this manuscript and approved its submission.
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Competing interests: Authors state no conflict of interest.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Ethical approval: The local Institutional Review Board deemed the study exempt from review.
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