| Presentation | 2019-12-19 病理画像癌種別領域分割のための癌種比率を活用した学習手法 Hiroki Tokunaga, Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose a new problem setting and method that uses cancer type ratio as weak supervision for semi-supervised learning. In order to perform pathological image segmentation using machine learning, a large amount of supervised data is required. In order to segment the image into cancer type region, the cancer type region is necessary. However, unlike a general image, a pathological image has very high resolution and the boundary between regions is unclear. Therefore, we propose a method to create supervised data from cancer type ratio information at low cost. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | PRMU2019-50 |
| Date of Issue | 2019-12-12 (PRMU) |
| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2019/12/19(2days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Chair | Yoichi Sato(Univ. of Tokyo) |
| Vice Chair | Toru Tamaki(Hiroshima Univ.) / Akisato Kimura(NTT) |
| Secretary | Toru Tamaki(NTT) / Akisato Kimura(OMRON SINICX) |
| Assistant | Yusuke Uchida(DeNA) / Takayoshi Yamashita(Chubu Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding |
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| Language | JPN-ONLY |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
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| 1st Author's Name | Hiroki Tokunaga |
| 1st Author's Affiliation | Kyushu University(Kyushu Univ.) |
| 2nd Author's Name | Yuki Teramoto |
| 2nd Author's Affiliation | Kyoto University Hospital(Kyoto University Hospital) |
| 3rd Author's Name | Akihiko Yoshizawa |
| 3rd Author's Affiliation | Kyoto University Hospital(Kyoto University Hospital) |
| 4th Author's Name | Ryoma Bise |
| 4th Author's Affiliation | Kyushu University/National Institute of Informatics(Kyushu Univ./NII) |
| Date | 2019-12-19 |
| Paper # | PRMU2019-50 |
| Volume (vol) | vol.119 |
| Number (no) | PRMU-347 |
| Page | pp.pp.23-27(PRMU), |
| #Pages | 5 |
| Date of Issue | 2019-12-12 (PRMU) |