論文
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2020年度発表論文
Journals(with referees)
| [1] | Titinunt Kitrungrotsakul, Xian-Hau Han, Yutaro Iwamoto, Satoko Takemoto, Hideo Yokota, Sari Ipponjima, Tomomi Nemoto, Wei Xiong, and *Yen-Wei Chen, “An End-to-End CNN and LSTM Network with 3D Anchors for Mitotic Cell Detection in 4D Microscopic Images and Its Parallel Implementation on Multiple GPUs,” Neural Computing and Applications, Vol.32, pp.5669-5679 (2020). (SCI, Impact factor: 4.664) (こちら) |
| [2] | Takuma Terada, Ryusuke Kimura, Yen-Wei Chen, “3D facial landmark detection based on differential cylindrical projection and multi-task learning,” Communications in Information and Systems, Vol.20, No.4, pp.443-459 (2020) (こちら) |
| [3] | Weibin Wang, Qingqinng Chen, Yutaro Iwamoto, Panyanat Aonpong, *Lanfen Lin, *Hongjie Hu, Qiaowei Zhang and *Yen-Wei Chen, et. al. “Deep Fusion Models of Multi-Phase CT and Selected Clinical Data for Preoperative Prediction of Early Recurrence in Hepatocellular Carcinoma,” IEEE Access, 2020 (SCI, Impact Factor: 3.75). (こちら) |
| [4] | Yu Song, Xu Qiao, Yutaro Iwamoto and Yen-Wei Chen, “Automatic Cephalometric Landmark Detection on X-ray Images Using a Deep-Learning Method,” Applied Sciences, Vol. 10, No.3, Applied Sciences, Vol. 10, 2547 (2020-4) (SCI, Impact factor: 2.474) (こちら) |
| [5] | Liying Peng, Lanfen Lin, Hongjie Hu, Yue Zhang, Huali Li, Yutaro Iwamoto, Xianhua Han, and Yen-Wei Chen, “Semi-supervised Learning for Semantic Segmentation of Emphysema with Partial Annotations,” IEEE Journal of Biomedical and Health Informatics, Vol.24, No.8, pp.2327-2326, 2020. (SCI, Impact factor: 5.2) (こちら) |
| [6] | Kenji Ono, Yutaro Iwamoto, and Yen-Wei Chen, Masahiro Nonaka, “Automatic Segmentation of Infant Brain Ventricles with Hydrocephalus in MRI Based on 2.5D U-Net and Transfer Learning,” Journal of Image and Graphics, Vol.8, No.2, pp.42-46, 2020. (こちら) |
| [7] | Fengchang Yang, Wei Chen, Haifeng Wei, Xianru Zhang, Shuanghu Yuan, Xu Qiao and Yen-wei Chen, “Machine Learning for histologic subtype classification of non-small cell lung cancer: A retrospective multicenter radiomics study,” Frontiers in Oncology, 2020 (Impact factor: 4.848) (こちら) |
| [8] | NasimNasiri, Amir Hossein Foruzan, Yen-Wei Chen, “Integration of a knowledge-based constraint into generative models with applications in semi-automatic segmentation of liver tumors,” Biomedical Signal Processing and Control, Vol.57, pp.??-?? (2020). (SCI, Impact factor: 2.943) (こちら) |
| [9] | Dong Liang, Yingying Xu, *Lanfeng Lin, Nan Zhou, *Hongjie Hu, Qiaowei Zhang, Qingqing Chen, Xianhua Han, Yutaro Iwamoto and *Yen-Wei Chen, “CasCRNN-GL-Net: cascaded convolutional and recurrent neural networks with global and local pathways for classification of focal liver lesions in multi-phase CT images,” Communications in Information and Systems, Vol.20, No.4, pp.415-442 (2020) (こちら) |
Proceedings of International Conference (with referees)
| [1] | Ryo Hasegawa, Yutaro IWAMOTO, Xianhua HAN, *Lanfen LIN, *Hongjie HU, Xiujun CAI, and *Yen-Wei CHEN, “Automatic Detection and Segmentation of Liver Tumors in Multi-Phase CT Images by Phase Attention Mask R-CNN,” Proc. of 39th IEEE International Conference on Consumer Electronics (IEEE ICCE2021), pp.1-4, online, Jan. 10-12, 2021. (こちら) |
| [2] | Rahul Kumar JAIN, Taro WATASUE, Tomohiro NAKAGAWA, Takahiro SATO, Yutaro Iwamoto, Xiang RUAN and Yen-Wei Chen, “LogoNet Layer-Aggregated Attention CenterNet for Logo Detection,” Proc. of 39th IEEE International Conference on Consumer Electronics (IEEE ICCE2021), pp.1-4, online, Jan. 10-12, 2021. (こちら) |
| [3] | Shaocong Mo, Ming Cai, Lanfen Lin, Ruofeng Tong, Qingqing Chen, Fang Wang, Hongjie Hu, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen, “Multimodal Priors Guided Segmentation of Liver Lesions in MRI Using Mutual Information Based Graph Co-Attention Networks,” In: Martel A.L. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12264. Springer, Cham. pp.429-438 (2020) (こちら) |
| [4] | Rui Xu, Tiantian Liu, Xinchen Ye, Lin Lin, Yen-Wei Chen, “Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network.” In: Martel A.L. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12265. Springer, Cham. pp.786-795 (2020)(こちら) |
| [5] | Yinhao Li, Yutaro Iwamoto, and Yen-Wei Chen, “A 3D Shrinking-and-Expanding Module with Channel Attention for Efficient Deep Learning-Based Super-Resolution,” in Y.-W. Chen et al. (eds.), Innovation in Medicine and Healthcare, Smart Innovation, Systems and Technologies 192 (Proc. of InMed2020), pp.117-125 (2020) (こちら) |
| [6] | Jia-Qing Liu, Yue Huang, Xin-Yin Huang, Xiao-Tong Xia, Xi-Xi Niu, Lanfen Lin, and Yen-Wei Chen, “Dynamic Facial Features in Positive-Emotional Speech for Identification of Depressive Tendencies” in Y.-W. Chen et al. (eds.), Innovation in Medicine and Healthcare, Smart Innovation, Systems and Technologies 192 (Proc. of InMed2020), pp.127-134 (2020) (こちら) |
| [7] | Panyanat Aonpong, Yutaro Iwamoto,Weibin Wang, Lanfen Lin,and Yen-Wei Chen, “Hand-Crafted and Deep Learning-Based Radiomics Models for Recurrence Prediction of Non-Small Cells Lung Cancers,” in Y.-W. Chen et al. (eds.), Innovation in Medicine and Healthcare, Smart Innovation, Systems and Technologies 192 (Proc. of InMed2020), pp.135-144 (2020) (こちら) |
| [8] | Huiming Huang, *Lanfen Lin, Ruofeng Tong, *Hongjie Hu, Qiaowei Zhang, Yutaro Iwamoto, Xian-Hua Han, *Yen-Wei Chen, Jian Wu, ”UNET 3+: A Full-Scale Connected UNET for Medical Image Segmentation,” Proc. of the 45th IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP2020), pp.1055-1059, Barcelona, Spain, May 4-8, 2020. (こちら) |
| [9] | Huiming Huang, *Lanfen Lin, Ruofeng Tong, *Hongjie Hu, Qiaowei Zhang, Yutaro Iwamoto, Xian-Hua Han, *Yen-Wei Chen, Jian Wu, ”WNET: An End-to-end Atlas-Guided and Boundary-Enhanced Network for for Medical Image Segmentation,” Proc. of IEEE International Symposium on Medical Imaging (IEEE ISBI2020), pp. 763-766, Iowa, USA, April 3-7, 2020.(こちら) |
| [10] | Kawahara Toshiki, Yinhao Li and Yutaro Iwamoto, Lanfen Lin, Yen-Wei Chen, “A Lightweight Deep Network for 3D Medical Image Segmentation,” Proc. of 2020 IEEE 8th Global Conference on Consumer Electronics (GCCE 2020), Kobe, Japan, Oct.12-14, 2020(こちら) |
| [11] | Toshiki Hazama, Masataka Seo, Yen-Wei Chen, “Generation of Figures with Controllable Posture Using Ss-InfoGAN,” Proc. of 2020 IEEE 8th Global Conference on Consumer Electronics (GCCE 2020), Kobe, Japan, Oct.12-14, 2020(こちら) |
| [12] | Kento Otsu, Masataka Seo, Toshihiro Kitajima, Yen-Wei Chen, “Automatic Generation of Eye Gaze Corrected Video Using Recursive Generative Adversarial Networks,” Proc. of 2020 IEEE 8th Global Conference on Consumer Electronics (GCCE 2020), Kobe, Japan, Oct.12-14, 2020(こちら) |
| [13] | Hikari Jinbo; Titinunt Kitrungrotsaku; Yutaro Iwamoto; Lanfen Lin; Hongjie Hu, Yen-Wei Chen, “Development of an Interactive Semantic Medical Image Segmentation System,” Proc. of 2020 IEEE 8th Global Conference on Consumer Electronics (GCCE 2020), Kobe, Japan, Oct.12-14, 2020(こちら) |
Proceedings of Domestic Conference (without referees)
| [1] | 川原稔暉, 井上明星，古川顕，岩本祐太郎, 陳延偉, “オプティカルフロー深層ネットワークを用いたCine-MRによる腹膜炎診断支援,” 日本生体医工学会生体画像と医用人工知能研究会, 2020.3.10. |
| [2] | Xinren Zhang, 岩本祐太郎, Jingliang Cheng, Jie Bai, Guohua Zhao, 韓先花, 陳 延偉, ”Modality-self Attentioonを用いた脳膠腫IDH遺伝子変異予測,” 日本生体医工学会生体画像と医用人工知能研究会, 2021.3.10. |
| [3] | He Li，岩本祐太郎, 韓先花, 陳延偉, “高効率かつ高精度な三次元ボリューム画像のセグメンテーション法,” 日本生体医工学会生体画像と医用人工知能研究会, 2021.3.10. |
| [4] | Weibin Wang, Qingqing Chen, Risheng Deng, Fang Wang, 岩本祐太郎, 韓先花, Lanfen Lin, 陳延偉, “Radiomicsと深層学習を用いたMR画像における肝臓癌の血管浸潤予測,” 日本生体医工学会生体画像と医用人工知能研究会, 2021.3.10. |
| [5] | 加藤瑞希, 岩本祐太郎, 杉本敏孝, 饗場徹, 陳延偉, “Attentionを付与したYOLO-v3による電動機コイルの不具合判定,” 映像情報メディア学会ヒューマンインフォメーション研究会, HI2021-7, 2021.3.5. |
| [6] | 木下将児, 劉家慶, 健山智子, 岩本祐太郎, 陳延偉, “木下将児,” 映像情報メディア学会ヒューマンインフォメーション研究会, HI2021-8, 2021.3.5. |
| [7] | 劉家慶, 黄越, 黄辛隠, 健山智子, 岩本祐太郎, 陳延偉, “CNNとTransformerエンコーダを用いたうつ状態の検出,” 電子情報通信学会パターン認識・メディア理解研究会, PRMU2020-83, 2021.3.4. (こちら) |
| [8] | Haohua Dong・Yutaro Iwamoto・Xianhua Han・Lanfen Lin・Hongjie Hu・Xiujun Cai・Yen-Wei Chen, “Case Discrimination: Self-supervised Learning for classification of Medical Image,” 電子情報通信学会パターン認識・メディア理解研究会, PRMU2020-64, 2020.12.17-18. (こちら) |
| [9] | 劉家慶, 黄越, 黄辛隠, 健山智子, 岩本祐太郎, 陳延偉, “センチメントテキスト朗読時の表情顔を用いたうつ状態の検出,” 電子情報通信学会パターン認識・メディア理解研究会, PRMU2020-32, 2020.10.9. (こちら) |
| [10] | 劉家慶, 健山智子, 岩本祐太郎, 陳延偉, “タッチベースインタラクティブCOVID-19のセグメンテーション、定量評価 および可視化システム,” 電子情報通信学会医用画像研究会, MI2020-20, 2020.9.3. (こちら) |
| [11] | Weibin Wang・Qingqing Chen・Fang Wang・Yutaro Iwamoto・Xianhua Han・Hongjie Hu・Lanfen Lin・Yen-Wei Chen, “Prediction of microvascular invasion in hepatocellular carcinoma based on radiomics method using MRI,” 電子情報通信学会医用画像研究会, MI2020-22, 2020.9.3. (こちら) |
| [12] | 永田敬之・岩本祐太郎・Zhao Ziyu・手塚祐司・岡田裕貴・前田清澄・和田厚幸・柏木厚典・陳延偉, “2段階セグメンテーションネットワークによる心外膜下脂肪組織の定量的解析とそのシステム開発,” 電子情報通信学会医用画像研究会, MI2020-23, 2020.9.3. (こちら) |
| [13] | 長谷川諒・岩本祐太郎・Lanfen Lin・Hongjie Hu・陳延偉, “Attention Mask R-CNNを用いたマルチフェ ーズCT画像における肝臓腫瘍候補の自動検出,” 電子情報通信学会医用画像研究会, MI2020-25, 2020.9.3. (こちら) |
| [14] | Yu Song・Xu Qiao・Yutaro Iwamoto・Yen-wei Chen, “Coarse-to-Fine Cephalometric Landmark Detection Using a Deep Learning Method,” 電子情報通信学会医用画像研究会, MI2020-26, 2020.9.3. (こちら) |