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| Search Results: Conference Papers |
| Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| ME |
2022-07-22
16:50 |
Online |
Online |
Deep Learning based Compressed Sensing Image Reconstruction Using Multiple Signal Under-sampling Pattern
Masaki Shibui, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.) |
CS-MRI, which is an application of compressed sensing (CS) to MR image acquisition, can reconstruct MR images from a sma... [more] |
ME2022-71
pp.27-29 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
13:15 |
Online |
online |
Compressive Sensing MR Reconstruction Using Generative Adversarial Network and Fresnel Transform of Images
Shinya Abe, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.) |
In recent years, there has been several researches on reconstruction methods using deep learning, which can significantl... [more] |
MMS2022-37 ME2022-62 AIT2022-37
pp.393-396 |
| ME |
2022-02-12
10:45 |
Online |
online |
Study on Deep Learning Reconstruction of MRI Complex Images Using Real-value CNN
Itona Fukatsu, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.) |
Application of compressed sensing has been applied to speed up the data acquisition time for MR imaging. In recent years... [more] |
ME2022-7
pp.25-27 |
| ME |
2021-07-16
14:00 |
Online |
Online |
Image Quality Improvements Using Half Fourier Encoding Method and Non-random Signal Under-sampling in CS-MRI Deep Learning Reconstruction
Yuta Miyamoto, Satoshi Ito (Utsunomiya Univ.) |
Compressed Sensing has the potential to reduce the scan time of MRI, and recently, deep learning has attract at tensions... [more] |
ME2021-63
pp.9-11 |
| ME |
2020-02-08
13:45 |
Kanagawa |
Kanto Gakuin University |
Study on Signal Under-sampling Pattern in Deep Learning Reconstruction for MR Compressed Sensing
Yuki Sato, Satoshi ITO (Utsunomiya Univ.) |
[more] |
ME2020-22
pp.75-76 |
| AIT, IIEEJ |
2016-08-26
14:55 |
Hokkaido |
FUTURE UNIVERSITY HAKODATE |
Compressed Sensing of 3D MR Phase-varied Images using Multi-scale eFREBAS Transform
Mone Shibuya, Satoshi Ito (Utsunomiya Univ.) |
[more] |
AIT2016-143
pp.23-26 |
| ME |
2015-12-10
14:55 |
Kanagawa |
Toin Univ. of Yokohama |
Accelerating Magnetic Resonance Three-Dimensional Imaging with Compressed Sensing and Multi-GPU Computing
Yuta Onodera, Satoshi Ito, Yoshifumi Yamada (Utsunomiya Univ.) |
Compressed sensing (CS) has inspired significant interest because of its potential to reduce data acquisition time. Howe... [more] |
ME2015-121
pp.17-21 |
| IEICE-HIP, CE, HI |
2013-11-19
13:50 |
Miyagi |
RIEC, Tohoku U. |
Perception of vocal expressions
-- Effects of age and radio listening --
Akihiro Tanaka (Tokyo Woman's christian Univ.), Satoshi Ito, Kenji Sotoya, Satoshi Ohkawara (Nippon Cultural Broadcasting inc), Katsumi Watanabe (Univ. of Tokyo) |
[more] |
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