Improvement of multisource localization of magnetic particles in an animal

Abstract In this simulation work, the linearized Bregman iterative algorithm was applied to solve the magnetic source distribution problem of a magnetic particle imaging (MPI) system for small animals. MPI system can apply an excitation magnetic field, and the induced magnetic field from the magneti...

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Autores principales:	Chin-Wei Lin, Shu-Hsien Liao, Han-Sheng Huang, Li-Min Wang, Jyh-Horng Chen, Chia-Hao Su, Kuen-Lin Chen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6722e93d48624e0eb6a28f00a35242cd
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spelling	oai:doaj.org-article:6722e93d48624e0eb6a28f00a35242cd2021-12-02T14:29:09ZImprovement of multisource localization of magnetic particles in an animal10.1038/s41598-021-88847-82045-2322https://doaj.org/article/6722e93d48624e0eb6a28f00a35242cd2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88847-8https://doaj.org/toc/2045-2322Abstract In this simulation work, the linearized Bregman iterative algorithm was applied to solve the magnetic source distribution problem of a magnetic particle imaging (MPI) system for small animals. MPI system can apply an excitation magnetic field, and the induced magnetic field from the magnetic nanoparticles (MNPs) can be detected by the sensors of MPI system. With a gaussian distribution source at the upper side of the mouse brain, sensors set above the mouse brain and the constant excitation magnetic field, the average deviation of the calculated source distribution from the multiplane scanning along the axis away from the mouse brain and the closest plane scanning are 2.78 × 10–3 and 2.84 × 10–3 respectively. The simulated result showed that combination of multiplane scanning hardly improves the accuracy of the source localization. In addition, a gradient scan method was developed that uses gradient magnetic field to scan the mouse brain. The position of the maximum of the lead field matrix will be controlled by the gradient field. With a set up gaussian distribution source at the bottom of the mouse brain, the average deviation of the calculated source distribution from the gradient scan method and the constant field are 4.42 × 10–2 and 5.05 × 10–2. The location error from the two method are 2.24 × 10–1 cm and 3.61 × 10–1 cm. The simulation showed that this method can improve the accuracy compared to constant field when the source is away from the sensor and having a potential for application.Chin-Wei LinShu-Hsien LiaoHan-Sheng HuangLi-Min WangJyh-Horng ChenChia-Hao SuKuen-Lin ChenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chin-Wei Lin Shu-Hsien Liao Han-Sheng Huang Li-Min Wang Jyh-Horng Chen Chia-Hao Su Kuen-Lin Chen Improvement of multisource localization of magnetic particles in an animal
description	Abstract In this simulation work, the linearized Bregman iterative algorithm was applied to solve the magnetic source distribution problem of a magnetic particle imaging (MPI) system for small animals. MPI system can apply an excitation magnetic field, and the induced magnetic field from the magnetic nanoparticles (MNPs) can be detected by the sensors of MPI system. With a gaussian distribution source at the upper side of the mouse brain, sensors set above the mouse brain and the constant excitation magnetic field, the average deviation of the calculated source distribution from the multiplane scanning along the axis away from the mouse brain and the closest plane scanning are 2.78 × 10–3 and 2.84 × 10–3 respectively. The simulated result showed that combination of multiplane scanning hardly improves the accuracy of the source localization. In addition, a gradient scan method was developed that uses gradient magnetic field to scan the mouse brain. The position of the maximum of the lead field matrix will be controlled by the gradient field. With a set up gaussian distribution source at the bottom of the mouse brain, the average deviation of the calculated source distribution from the gradient scan method and the constant field are 4.42 × 10–2 and 5.05 × 10–2. The location error from the two method are 2.24 × 10–1 cm and 3.61 × 10–1 cm. The simulation showed that this method can improve the accuracy compared to constant field when the source is away from the sensor and having a potential for application.
format	article
author	Chin-Wei Lin Shu-Hsien Liao Han-Sheng Huang Li-Min Wang Jyh-Horng Chen Chia-Hao Su Kuen-Lin Chen
author_facet	Chin-Wei Lin Shu-Hsien Liao Han-Sheng Huang Li-Min Wang Jyh-Horng Chen Chia-Hao Su Kuen-Lin Chen
author_sort	Chin-Wei Lin
title	Improvement of multisource localization of magnetic particles in an animal
title_short	Improvement of multisource localization of magnetic particles in an animal
title_full	Improvement of multisource localization of magnetic particles in an animal
title_fullStr	Improvement of multisource localization of magnetic particles in an animal
title_full_unstemmed	Improvement of multisource localization of magnetic particles in an animal
title_sort	improvement of multisource localization of magnetic particles in an animal
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6722e93d48624e0eb6a28f00a35242cd
work_keys_str_mv	AT chinweilin improvementofmultisourcelocalizationofmagneticparticlesinananimal AT shuhsienliao improvementofmultisourcelocalizationofmagneticparticlesinananimal AT hanshenghuang improvementofmultisourcelocalizationofmagneticparticlesinananimal AT liminwang improvementofmultisourcelocalizationofmagneticparticlesinananimal AT jyhhorngchen improvementofmultisourcelocalizationofmagneticparticlesinananimal AT chiahaosu improvementofmultisourcelocalizationofmagneticparticlesinananimal AT kuenlinchen improvementofmultisourcelocalizationofmagneticparticlesinananimal
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Improvement of multisource localization of magnetic particles in an animal

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