| Paper Abstract and Keywords |
| Presentation |
2021-07-16 13:30
High-resolution ultrasound imaging with efficient synthesis of transmission angles and frequency subbands based on deep learning
Emi Aiura, Yuta Saito, Norio Tagawa (Tokyo Metro Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Ultrasound imaging is widely used in the medical field because it is non-invasive and can be imaged in real time. We have proposed a high-resolution ultrasound imaging method (FPWC-MVDR) using an adaptive compound of the ultrasonic transmission direction and frequency sub-band. This method can improve image quality compared to delay-and-sum beamforming, but since the optimal compound weights are determined for each pixel, the amount of calculation is large and there is a concern that the frame rate may decrease. Therefore, in this study, we realize high frame rate using deep learning. We evaluate the performance using the data set obtained in the experiment. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Array Transducer / Beamforming / Compound / Deep Learning / / / / |
| Reference Info. |
ITE Tech. Rep., vol. 45, no. 18, ME2021-62, pp. 5-7, July 2021. |
| Paper # |
ME2021-62 |
| 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) |
High-resolution ultrasound imaging with efficient synthesis of transmission angles and frequency subbands based on deep learning |
| Sub Title (in English) |
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| Keyword(1) |
Array Transducer |
| Keyword(2) |
Beamforming |
| Keyword(3) |
Compound |
| Keyword(4) |
Deep Learning |
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| 1st Author's Name |
Emi Aiura |
| 1st Author's Affiliation |
Tokyo Metropolitan University (Tokyo Metro Univ.) |
| 2nd Author's Name |
Yuta Saito |
| 2nd Author's Affiliation |
Tokyo Metropolitan University (Tokyo Metro Univ.) |
| 3rd Author's Name |
Norio Tagawa |
| 3rd Author's Affiliation |
Tokyo Metropolitan University (Tokyo Metro Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2021-07-16 13:30:00 |
| Presentation Time |
30 minutes |
| Registration for |
ME |
| Paper # |
ME2021-62 |
| Volume (vol) |
vol.45 |
| Number (no) |
no.18 |
| Page |
pp.5-7 |
| #Pages |
3 |
| Date of Issue |
2021-07-09 (ME) |