| Presentation | 2018-09-21 [Short Paper] Automatic Segmentation of Epicardial Using Deep Learning Ziyu Zhao, Tomoe Otoishi, Yutaro Iwamoto, Youji Tetsuka, Yuki Okada, Kiyosumi Maeda, Atsuyuki Wada, Atsunori Kashiwagi, Yanwei Chen, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The epicardial is a wall sac containing the heart and the roots of the great vessels. Epicardial adipose tissue adhere to the inside and outside of the epicardial, it is necessary to extract the epicardial to distinguish these fat tissues. A major challenge in epicardial segmentation is that in the cardiac Computed Tomography(CT) images, the epicardial exists as a very thin line and there are places where it can not be observed. Up to now, the main method of epicardial segmentation is manual extraction by experts. In this study, we propose a fully automatic method for epicardial segmentation, which is developed using U-Net, and demonstrated that it is possible to automatically segment epicardial. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep learning / Epicardial segmentation / U-Net |
| Paper # | PRMU2018-55,IBISML2018-32 |
| Date of Issue | 2018-09-13 (PRMU, IBISML) |
| Conference Information | |
| Committee | PRMU / IBISML / IPSJ-CVIM |
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| Conference Date | 2018/9/20(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Shinichi Sato(NII) / Hisashi Kashima(Kyoto Univ.) |
| Vice Chair | Yoshihisa Ijiri(Omron) / Toru Tamaki(Hiroshima Univ.) / Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Yoshihisa Ijiri(NEC) / Toru Tamaki(Osaka Univ.) / Masashi Sugiyama(Nagoya Inst. of Tech.) / Koji Tsuda(AIST) |
| Assistant | Go Irie(NTT) / Yoshitaka Ushiku(Univ. of Tokyo) / Tomoharu Iwata(NTT) / Shigeyuki Oba(Kyoto Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / Special Interest Group on Computer Vision and Image Media |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Short Paper] Automatic Segmentation of Epicardial Using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | Deep learning |
| Keyword(2) | Epicardial segmentation |
| Keyword(3) | U-Net |
| 1st Author's Name | Ziyu Zhao |
| 1st Author's Affiliation | Ritsumei University(Ritsumei Univ) |
| 2nd Author's Name | Tomoe Otoishi |
| 2nd Author's Affiliation | Ritsumei University(Ritsumei Univ) |
| 3rd Author's Name | Yutaro Iwamoto |
| 3rd Author's Affiliation | Ritsumei University(Ritsumei Univ) |
| 4th Author's Name | Youji Tetsuka |
| 4th Author's Affiliation | Kusatsu General Hospital(Kusatsu General Hospita) |
| 5th Author's Name | Yuki Okada |
| 5th Author's Affiliation | Kusatsu General Hospital(Kusatsu General Hospita) |
| 6th Author's Name | Kiyosumi Maeda |
| 6th Author's Affiliation | Kusatsu General Hospital(Kusatsu General Hospita) |
| 7th Author's Name | Atsuyuki Wada |
| 7th Author's Affiliation | Kusatsu General Hospital(Kusatsu General Hospita) |
| 8th Author's Name | Atsunori Kashiwagi |
| 8th Author's Affiliation | Kusatsu General Hospital(Kusatsu General Hospita) |
| 9th Author's Name | Yanwei Chen |
| 9th Author's Affiliation | Ritsumei University(Ritsumei Univ) |
| Date | 2018-09-21 |
| Paper # | PRMU2018-55,IBISML2018-32 |
| Volume (vol) | vol.118 |
| Number (no) | PRMU-219,IBISML-220 |
| Page | pp.pp.131-132(PRMU), pp.131-132(IBISML), |
| #Pages | 2 |
| Date of Issue | 2018-09-13 (PRMU, IBISML) |