| Presentation | 2021-12-17 Data Augmentation to Robust Deep Learning-Based Lesion Classification for CT Image with Different Imaging Conditions Nobuhiro Miyazaki, Hiroaki Takebe, Takayuki Baba, Hiroaki Terada, Toru Higaki, Kazuo Awai, Masahiko Shimada, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, we propose a data augmentation to robust DL (deep learning)-based lesion classification for CT image with different imaging condition. The accuracy of DL results must be maintained when features of the target image differ from features of training image created on different CT scanners. The PSF (Point Spread Function) of the scanner-specific reconstruction kernel, which emphasizes specific targets, account for such differences. Our method cancels specific PSF at CT imaging and generates multiple training image with various features based on different types of PSF. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | CT Image / Deep Learning / Data Augmentation / Point Spread Function |
| Paper # | PRMU2021-48 |
| Date of Issue | 2021-12-09 (PRMU) |
| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2021/12/16(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Seiichi Uchida(Kyushu Univ.) |
| Vice Chair | Masakazu Iwamura(Osaka Pref. Univ.) / Mitsuru Anpai(Denso IT Lab.) |
| Secretary | Masakazu Iwamura(NTT) / Mitsuru Anpai(Tottori Univ.) |
| Assistant | Kouta Yamaguchi(CyberAgent) / Yusuke Matsui(Univ. of Tokyo) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Data Augmentation to Robust Deep Learning-Based Lesion Classification for CT Image with Different Imaging Conditions |
| Sub Title (in English) | |
| Keyword(1) | CT Image |
| Keyword(2) | Deep Learning |
| Keyword(3) | Data Augmentation |
| Keyword(4) | Point Spread Function |
| 1st Author's Name | Nobuhiro Miyazaki |
| 1st Author's Affiliation | FUJITSU LIMITED(FUJITSU) |
| 2nd Author's Name | Hiroaki Takebe |
| 2nd Author's Affiliation | FUJITSU LIMITED(FUJITSU) |
| 3rd Author's Name | Takayuki Baba |
| 3rd Author's Affiliation | FUJITSU LIMITED(FUJITSU) |
| 4th Author's Name | Hiroaki Terada |
| 4th Author's Affiliation | Hiroshima University(Hiroshima Univ.) |
| 5th Author's Name | Toru Higaki |
| 5th Author's Affiliation | Hiroshima University(Hiroshima Univ.) |
| 6th Author's Name | Kazuo Awai |
| 6th Author's Affiliation | Hiroshima University(Hiroshima Univ.) |
| 7th Author's Name | Masahiko Shimada |
| 7th Author's Affiliation | Fujitsu Japan Limited(Fujitsu Japan) |
| Date | 2021-12-17 |
| Paper # | PRMU2021-48 |
| Volume (vol) | vol.121 |
| Number (no) | PRMU-304 |
| Page | pp.pp.130-135(PRMU), |
| #Pages | 6 |
| Date of Issue | 2021-12-09 (PRMU) |