Paper Abstract and Keywords |
Presentation |
2022-02-12 10:45
Study on Deep Learning Reconstruction of MRI Complex Images Using Real-value CNN Itona Fukatsu, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Application of compressed sensing has been applied to speed up the data acquisition time for MR imaging. In recent years, research on reconstruction method using deep learning has been actively studied to reduce the reconstruction time and to improve the quality of reconstructed images. Since MR images are complex-value images, CNN needs to deal with complex values. In this study, we propose a new method for reconstructing complex-value images using a real-value CNN by introducing symmetrical signal under-sampling. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
MRI / CNN / image reconstruction / high-speed imaging / / / / |
Reference Info. |
ITE Tech. Rep., vol. 46, no. 4, ME2022-7, pp. 25-27, Feb. 2022. |
Paper # |
ME2022-7 |
Date of Issue |
2022-02-05 (ME) |
ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
Download PDF |
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Conference Information |
Committee |
ME |
Conference Date |
2022-02-12 - 2022-02-12 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
ME |
Conference Code |
2022-02-ME |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Study on Deep Learning Reconstruction of MRI Complex Images Using Real-value CNN |
Sub Title (in English) |
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MRI |
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CNN |
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image reconstruction |
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high-speed imaging |
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1st Author's Name |
Itona Fukatsu |
1st Author's Affiliation |
Ustunomiya University (Utsunomiya Univ.) |
2nd Author's Name |
Kazuki Yamato |
2nd Author's Affiliation |
Ustunomiya University (Utsunomiya Univ.) |
3rd Author's Name |
Satoshi Ito |
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Ustunomiya University (Utsunomiya Univ.) |
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Speaker |
Author-1 |
Date Time |
2022-02-12 10:45:00 |
Presentation Time |
15 minutes |
Registration for |
ME |
Paper # |
ME2022-7 |
Volume (vol) |
vol.46 |
Number (no) |
no.4 |
Page |
pp.25-27 |
#Pages |
3 |
Date of Issue |
2022-02-05 (ME) |