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Research on innovative signal analysis for real-time magnetic resonance imaging of extremely small areas

Research Project

Project/Area Number 18H03259
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 61010:Perceptual information processing-related
Research InstitutionUniversity of Toyama

Principal Investigator

Hirobayashi Shigeki  富山大学, 学術研究部工学系, 教授 (40272950)

Project Period (FY) 2018-04-01 – 2021-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥17,680,000 (Direct Cost: ¥13,600,000、Indirect Cost: ¥4,080,000)
Fiscal Year 2020: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2019: ¥5,590,000 (Direct Cost: ¥4,300,000、Indirect Cost: ¥1,290,000)
Fiscal Year 2018: ¥10,010,000 (Direct Cost: ¥7,700,000、Indirect Cost: ¥2,310,000)
Keywords信号処理 / MRI / 断層撮影技術
Outline of Final Research Achievements

In this study, the spatial resolution of the existing 1.5 T magnetic resonance imaging (MRI) was attempted to be improved from 0.7 mm to 50 μm by accurately analyzing the MRI signal using high-precision signal analysis.
In experiment, MRI measurement data is analyzed by each method; fast Fourier transform (FFT) commonly used for MRI image reconstruction, interpolation method, NHA. MRI images were reconstructed and compared based on the analysis results of each method.From the experimental results, in the MRI image by FFT and interpolation method, the resolution was insufficient, and the sidelobes smoothed out the intensity values, making it impossible to confirm the detailed water distribution. On the other hand, the MRI image by NHA greatly suppressed the occurrence of sidelobes by accurately analyzing the measurement data, and locations that were blocky in the FFT were divided into multiple intensity values.

Academic Significance and Societal Importance of the Research Achievements

MRIは、非侵襲的に物体内を可視化できるため幅広く活用されており、MRIで計測した信号は一般的にFFTを用いて画像へ再構成している。このFFTに代わって、NHAを応用することで、設備はそのままで性能を極限まで高め、低磁場でこれまで以上の空間分解能を実現できる可能性を示した。

Report

(4 results)
  • 2021 Final Research Report ( PDF )
  • 2020 Annual Research Report
  • 2019 Annual Research Report
  • 2018 Annual Research Report

URL: 

Published: 2018-04-23   Modified: 2023-01-30  

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