| Paper Abstract and Keywords |
| Presentation |
2021-07-16 14:00
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.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Compressed Sensing has the potential to reduce the scan time of MRI, and recently, deep learning has attract at tensions for reconstructing high quality images. In the application of CS to MR imaging, data acquisition points are skipped randomly in signal space. Generally, image quality improves in proportion to the sampling density of signal. Half Fourier imaging (HF) is well-known MR fast imaging method in which almost half of the signal in signal space are acquired. When CS is combined with HF, image quality improvement is expected with the increase of the sampling density which is achieved by acquiring a given number of signals on one side of the signal space. In this study, we discuss the image quality obtained in deep learning reconstruction for CS with HF using random or regular under-sampling patterns. It was shown that higher quality images were obtained when HF were combined with CS and regular under-sampling patterns were used. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Deep Learning / Compressed Sensing / Half Fourier Encoding / MRI / / / / |
| Reference Info. |
ITE Tech. Rep., vol. 45, no. 18, ME2021-63, pp. 9-11, July 2021. |
| Paper # |
ME2021-63 |
| Date of Issue |
2021-07-09 (ME) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
ME |
| Conference Date |
2021-07-16 - 2021-07-16 |
| 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 |
2021-07-ME |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Image Quality Improvements Using Half Fourier Encoding Method and Non-random Signal Under-sampling in CS-MRI Deep Learning Reconstruction |
| Sub Title (in English) |
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| Keyword(1) |
Deep Learning |
| Keyword(2) |
Compressed Sensing |
| Keyword(3) |
Half Fourier Encoding |
| Keyword(4) |
MRI |
| Keyword(5) |
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| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Yuta Miyamoto |
| 1st Author's Affiliation |
Utsunomiya University (Utsunomiya Univ.) |
| 2nd Author's Name |
Satoshi Ito |
| 2nd Author's Affiliation |
Utsunomiya University (Utsunomiya Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2021-07-16 14:00:00 |
| Presentation Time |
30 minutes |
| Registration for |
ME |
| Paper # |
ME2021-63 |
| Volume (vol) |
vol.45 |
| Number (no) |
no.18 |
| Page |
pp.9-11 |
| #Pages |
3 |
| Date of Issue |
2021-07-09 (ME) |