| Presentation | 2018-09-21 [Short Paper] Computer-Aided Diagnosis of Liver Cancers Using Deep Learning with Fine-tuning Weibin Wang, Dong Liang, Lanfen Lin, Hongjie Hu, Qiaowei Zhang, Qingqing Chen, Yutaro lwamoto, Xianhua Han, Yen-Wei Chen, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Liver cancer is one of the leading causes of death world-wide. Computer-aided diagnosis plays an important role in liver lesion diagnosis (classification). Recently, several deep learning-based computer-aided diagnosis systems have been proposed for classification of liver lesions and their effectiveness have been demonstrated. The main challenge in deep learning-based medical image classification is the lack of annotated training samples. In this paper, we demonstrated that fine-tuning can significantly improve the liver lesion classification accuracy especially for the small training samples. We used the residual convolutional neural network (ResNet), which is the state-of-the-art network, as our baseline network for focal liver lesion classification on multi-phase CT images. The fine-tuning significantly improved the classification accuracy from 83.7% to 91.2%. The classification accuracy (91.2%) is higher than the accuracy of the state-of-the-art methods. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | ResNetLiver cancer classificationMulti-phase CTFine-tuning |
| Paper # | PRMU2018-57,IBISML2018-34 |
| 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 | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Short Paper] Computer-Aided Diagnosis of Liver Cancers Using Deep Learning with Fine-tuning |
| Sub Title (in English) | |
| Keyword(1) | ResNetLiver cancer classificationMulti-phase CTFine-tuning |
| 1st Author's Name | Weibin Wang |
| 1st Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| 2nd Author's Name | Dong Liang |
| 2nd Author's Affiliation | Zhejiang University(Zhejiang Univ.) |
| 3rd Author's Name | Lanfen Lin |
| 3rd Author's Affiliation | Zhejiang University(Zhejiang Univ.) |
| 4th Author's Name | Hongjie Hu |
| 4th Author's Affiliation | Zhejiang University(Zhejiang Univ.) |
| 5th Author's Name | Qiaowei Zhang |
| 5th Author's Affiliation | Zhejiang University(Zhejiang Univ.) |
| 6th Author's Name | Qingqing Chen |
| 6th Author's Affiliation | Zhejiang University(Zhejiang Univ.) |
| 7th Author's Name | Yutaro lwamoto |
| 7th Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| 8th Author's Name | Xianhua Han |
| 8th Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| 9th Author's Name | Yen-Wei Chen |
| 9th Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| Date | 2018-09-21 |
| Paper # | PRMU2018-57,IBISML2018-34 |
| Volume (vol) | vol.118 |
| Number (no) | PRMU-219,IBISML-220 |
| Page | pp.pp.139-140(PRMU), pp.139-140(IBISML), |
| #Pages | 2 |
| Date of Issue | 2018-09-13 (PRMU, IBISML) |