IEICE TRANSACTIONS on Information
Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging
Summary :
Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function–defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.3 pp.872-879
- Publication Date
- 2012/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.872
- Type of Manuscript
- PAPER
- Category
- Biological Engineering
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Keyword
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Yasutoshi ISHIHARA, Tsuyoshi KUWABARA, Takumi HONMA, Yohei NAKAGAWA, "Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 3, pp. 872-879, March 2012, doi: 10.1587/transinf.E95.D.872.
Abstract: Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function–defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.872/_p
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@ARTICLE{e95-d_3_872,
author={Yasutoshi ISHIHARA, Tsuyoshi KUWABARA, Takumi HONMA, Yohei NAKAGAWA, },
journal={IEICE TRANSACTIONS on Information},
title={Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging},
year={2012},
volume={E95-D},
number={3},
pages={872-879},
abstract={Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function–defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.},
keywords={},
doi={10.1587/transinf.E95.D.872},
ISSN={1745-1361},
month={March},}
Copy
TY - JOUR
TI - Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging
T2 - IEICE TRANSACTIONS on Information
SP - 872
EP - 879
AU - Yasutoshi ISHIHARA
AU - Tsuyoshi KUWABARA
AU - Takumi HONMA
AU - Yohei NAKAGAWA
PY - 2012
DO - 10.1587/transinf.E95.D.872
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2012
AB - Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function–defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.
ER -
English
