Averaging Randomized Kaczmarz for Magnetic Particle Imaging

Yimeng Li; Peng Zhang; Hui Hui; Lin Yin; Jie Tian

doi:10.18416/ijmpi.2022.2203032

Averaging Randomized Kaczmarz for Magnetic Particle Imaging

Yimeng Li
, Peng Zhang
, Hui Hui
, Lin Yin
, Jie Tian^*

^*Corresponding author for this work

School of Engineering Medicine

Beihang University
CAS - Institute of Automation
Beijing Jiaotong University

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Magnetic particle imaging (MPI) is a promising modality for medical imaging with high resolution and sensitivity. In this paper, the averaging randomized Kaczmarz (ARK) reconstruction method is proposed to accelerate the image reconstruction process. Compared with the traditional Kaczmarz method, the ARK algorithm improves the image quality and reconstruction resolution. The iterative parameters of the ARK are selected, and further optimization needs to be studied.

Original language	English
Article number	2203032
Journal	International Journal on Magnetic Particle Imaging
Volume	8
Issue number	1
DOIs	https://doi.org/10.18416/ijmpi.2022.2203032
State	Published - 2022

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10.18416/ijmpi.2022.2203032

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@article{688e5585e7d3469ebfaa307c63398365,

title = "Averaging Randomized Kaczmarz for Magnetic Particle Imaging",

abstract = "Magnetic particle imaging (MPI) is a promising modality for medical imaging with high resolution and sensitivity. In this paper, the averaging randomized Kaczmarz (ARK) reconstruction method is proposed to accelerate the image reconstruction process. Compared with the traditional Kaczmarz method, the ARK algorithm improves the image quality and reconstruction resolution. The iterative parameters of the ARK are selected, and further optimization needs to be studied.",

author = "Yimeng Li and Peng Zhang and Hui Hui and Lin Yin and Jie Tian",

note = "Publisher Copyright: {\textcopyright} 2022 Infinite Science Publishing.",

year = "2022",

doi = "10.18416/ijmpi.2022.2203032",

language = "英语",

volume = "8",

journal = "International Journal on Magnetic Particle Imaging",

issn = "2365-9033",

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T1 - Averaging Randomized Kaczmarz for Magnetic Particle Imaging

AU - Li, Yimeng

AU - Zhang, Peng

AU - Hui, Hui

AU - Yin, Lin

AU - Tian, Jie

PY - 2022

Y1 - 2022

N2 - Magnetic particle imaging (MPI) is a promising modality for medical imaging with high resolution and sensitivity. In this paper, the averaging randomized Kaczmarz (ARK) reconstruction method is proposed to accelerate the image reconstruction process. Compared with the traditional Kaczmarz method, the ARK algorithm improves the image quality and reconstruction resolution. The iterative parameters of the ARK are selected, and further optimization needs to be studied.

AB - Magnetic particle imaging (MPI) is a promising modality for medical imaging with high resolution and sensitivity. In this paper, the averaging randomized Kaczmarz (ARK) reconstruction method is proposed to accelerate the image reconstruction process. Compared with the traditional Kaczmarz method, the ARK algorithm improves the image quality and reconstruction resolution. The iterative parameters of the ARK are selected, and further optimization needs to be studied.

UR - https://www.scopus.com/pages/publications/85128267039

U2 - 10.18416/ijmpi.2022.2203032

DO - 10.18416/ijmpi.2022.2203032

M3 - 文章

AN - SCOPUS:85128267039

SN - 2365-9033

VL - 8

JO - International Journal on Magnetic Particle Imaging

JF - International Journal on Magnetic Particle Imaging

IS - 1

M1 - 2203032

ER -

Averaging Randomized Kaczmarz for Magnetic Particle Imaging

Abstract

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