Narrow-Band Magnetic Nanoparticle Imaging using Orthogonal Gradient Field
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- Bai Shi
- Graduate School of Information Science and Electrical Engineering, Kyushu University
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- Hirokawa Aiki
- Graduate School of Information Science and Electrical Engineering, Kyushu University
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- Tanabe Kazuhiro
- Graduate School of Information Science and Electrical Engineering, Kyushu University
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- Sasayama Teruyoshi
- Graduate School of Information Science and Electrical Engineering, Kyushu University
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- Yoshida Takashi
- Graduate School of Information Science and Electrical Engineering, Kyushu University
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- Enpuku Keiji
- Graduate School of Information Science and Electrical Engineering, Kyushu University
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Abstract
Magnetic particle imaging (MPI) utilizing nonlinear magnetization of magnetic nanoparticles (MNPs) is a new technique for in vivo diagnosis in medical imaging. We have improved a narrow-band MPI system using an orthogonal gradient field and third-harmonic signal detection. An AC excitation field with Bac = 1 mT and f = 22.75 kHz was applied, and a third-harmonic signal from MNPs (f = 68.75 kHz) was detected. The sensitivity of detection was improved by choosing proper diameter of a pickup coil so that we could detect 100 μg of MNPs located as deep as z = 50 mm. A spatial resolution of ~4 mm was achieved by using a gradient field of 1 T/m. We demonstrated the detection of two MNP samples spaced 5 mm apart and located at z = 50 mm. The measured contour map of the voltage signal was converted to an MNP distribution using the singular value decomposition (SVD) method. We were able to accurately identify two MNP samples. We also demonstrate the imaging of the letter "K" composed of eleven MNP samples with 7-mm spacing, which demonstrated the validity of the present method.
Journal
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- Journal of the Magnetics Society of Japan
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Journal of the Magnetics Society of Japan 39 (5), 216-219, 2015
The Magnetics Society of Japan
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Details 詳細情報について
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- CRID
- 1390282680264526208
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- NII Article ID
- 130005102241
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- NII Book ID
- AA12297999
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- ISSN
- 18822932
- 18822924
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- NDL BIB ID
- 026726111
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed