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ORCIDNoriyuki Tomiyama
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2020 – today
- 2024
[j11]Kosuke Kita
, Takahito Fujimori, Yuki Suzuki, Takashi Kaito, Shota Takenaka, Yuya Kanie, Masayuki Furuya, Tomohiro Wataya, Daiki Nishigaki, Junya Sato, Noriyuki Tomiyama, Seiji Okada, Shoji Kido:
Automated entry of paper-based patient-reported outcomes: Applying deep learning to the Japanese orthopaedic association back pain evaluation questionnaire. Comput. Biol. Medicine 172: 108197 (2024)- 2023
- [c21]Keita Otani, Daiki Nishigaki, Taro Hatsutani, Takeshi Takamoto, Yuki Suzuki, Shoji Kido, Noriyuki Tomiyama:
Automatic characterization of liver tumors from multi-phase CT images. Medical Imaging: Computer-Aided Diagnosis 2023 - [c20]Akimichi Ichinose, Taro Hatsutani, Keigo Nakamura, Yoshiro Kitamura, Satoshi Iizuka, Edgar Simo-Serra, Shoji Kido, Noriyuki Tomiyama:
Visual Grounding of Whole Radiology Reports for 3D CT Images. MICCAI (5) 2023: 611-621 - [i3]Akimichi Ichinose, Taro Hatsutani, Keigo Nakamura, Yoshiro Kitamura, Satoshi Iizuka, Edgar Simo-Serra, Shoji Kido, Noriyuki Tomiyama:
Visual Grounding of Whole Radiology Reports for 3D CT Images. CoRR abs/2312.04794 (2023) - 2022
- [j10]Shoji Kido, Shunske Kidera, Yasushi Hirano, Shingo Mabu, Tohru Kamiya, Nobuyuki Tanaka, Yuki Suzuki, Yanagawa Masahiro, Noriyuki Tomiyama:
Segmentation of Lung Nodules on CT Images Using a Nested Three-Dimensional Fully Connected Convolutional Network. Frontiers Artif. Intell. 5: 782225 (2022) - [c19]Toru Nishino, Yasuhide Miura, Tomoki Taniguchi, Tomoko Ohkuma, Yuki Suzuki, Shoji Kido, Noriyuki Tomiyama:
Factual Accuracy is not Enough: Planning Consistent Description Order for Radiology Report Generation. EMNLP 2022: 7123-7138 - [c18]Rui Xu, Yufeng Wang, Xinchen Ye, Pengcheng Wu, Yen-Wei Chen, Fangyi Xu, Wenchao Zhu, Chao Chen, Yong Zhou, Hongjie Hu, Xiaofeng Qu, Shoji Kido, Noriyuki Tomiyama:
Pixel-Level and Affinity-Level Knowledge Distillation for Unsupervised Segmentation of Covid-19 Lesions. ICASSP 2022: 1376-1380 - [i2]Junya Sato, Yuki Suzuki, Tomohiro Wataya, Daiki Nishigaki, Kosuke Kita, Kazuki Yamagata, Noriyuki Tomiyama, Shoji Kido:
Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest Radiographs. CoRR abs/2205.04282 (2022) - 2021
- [j9]Kento Sugimoto, Toshihiro Takeda, Jong-Hoon Oh, Shoya Wada, Shozo Konishi, Asuka Yamahata, Shiro Manabe, Noriyuki Tomiyama, Takashi Matsunaga, Katsuyuki Nakanishi, Yasushi Matsumura:
Extracting clinical terms from radiology reports with deep learning. J. Biomed. Informatics 116: 103729 (2021) - 2020
- [j8]Rui Xu, Zhen Cong, Xinchen Ye, Yasushi Hirano, Shoji Kido, Tomoko Gyobu, Yutaka Kawata, Osamu Honda, Noriyuki Tomiyama:
Pulmonary Textures Classification via a Multi-Scale Attention Network. IEEE J. Biomed. Health Informatics 24(7): 2041-2052 (2020) - [c17]Rui Xu, Zhen Cong, Xinchen Ye, Shoji Kido, Noriyuki Tomiyama:
Unsupervised Content-Preserved Adaptation Network for Classification of Pulmonary Textures from Different CT Scanners. ICASSP 2020: 1060-1064 - [c16]Rui Xu, Yi Wang, Tiantian Liu, Xinchen Ye, Lin Lin, Yen-Wei Chen, Shoji Kido, Noriyuki Tomiyama:
BG-Net: Boundary-Guided Network for Lung Segmentation on Clinical CT Images. ICPR 2020: 8782-8788 - [c15]Xinchen Ye, Yuyao Xu, Rui Xu, Shoji Kido, Noriyuki Tomiyama:
Detail- Revealing Deep Low-Dose CT Reconstruction. ICPR 2020: 8789-8796 - [c14]Rui Xu, Xiao Cao, Yufeng Wang, Yen-Wei Chen, Xinchen Ye, Lin Lin, Wenchao Zhu, Chao Chen, Fangyi Xu, Yong Zhou, Hongjie Hu, Shoji Kido, Noriyuki Tomiyama:
Unsupervised Detection of Pulmonary Opacities for Computer-Aided Diagnosis of COVID-19 on CT Images. ICPR 2020: 9007-9014 - [c13]Yuki Suzuki, Kazuki Yamagata, Yanagawa Masahiro, Shoji Kido, Noriyuki Tomiyama:
Weak supervision in convolutional neural network for semantic segmentation of diffuse lung diseases using partially annotated dataset. Medical Imaging: Computer-Aided Diagnosis 2020 - [i1]Yuki Suzuki, Kazuki Yamagata, Yanagawa Masahiro, Shoji Kido, Noriyuki Tomiyama:
Weak Supervision in Convolutional Neural Network for Semantic Segmentation of Diffuse Lung Diseases Using Partially Annotated Dataset. CoRR abs/2002.11936 (2020)
2010 – 2019
- 2019
- [j7]Mazen Soufi, Yoshito Otake, Masatoshi Hori, Kazuya Moriguchi, Yasuharu Imai, Yoshiyuki Sawai, Takashi Ota, Noriyuki Tomiyama, Yoshinobu Sato:
Liver shape analysis using partial least squares regression-based statistical shape model: application for understanding and staging of liver fibrosis. Int. J. Comput. Assist. Radiol. Surg. 14(12): 2083-2093 (2019) - [c12]Yuchen Wang, Ze Jin, Yukiko Tokuda, Yasuto Naoi, Noriyuki Tomiyama, Kenji Suzuki:
Development of Deep-learning Segmentation for Breast Cancer in MR Images based on Neural Network Convolution. ICCPR 2019: 187-191 - 2016
- [j6]Yoshiyuki Kagiyama, Itaru Otomaru, Masaki Takao, Nobuhiko Sugano, Masahiko Nakamoto, Futoshi Yokota, Noriyuki Tomiyama, Yukio Tada, Yoshinobu Sato:
CT-based automated planning of acetabular cup for total hip arthroplasty (THA) based on hybrid use of two statistical atlases. Int. J. Comput. Assist. Radiol. Surg. 11(12): 2253-2271 (2016) - [c11]Shunta Hirayama, Yoshito Otake, Toshiyuki Okada, Masatoshi Hori, Noriyuki Tomiyama, Yoshinobu Sato:
Automated segmentation of upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ interrelations. Medical Imaging: Image Processing 2016: 97840F - 2015
- [j5]Toshiyuki Okada, Marius George Linguraru, Masatoshi Hori, Ronald M. Summers, Noriyuki Tomiyama, Yoshinobu Sato:
Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors. Medical Image Anal. 26(1): 1-18 (2015) - 2014
- [j4]Amir Hossein Foruzan, Yen-Wei Chen, Masatoshi Hori, Yoshinobu Sato, Noriyuki Tomiyama:
Capturing large shape variations of liver using population-based statistical shape models. Int. J. Comput. Assist. Radiol. Surg. 9(6): 967-977 (2014) - [j3]Junping Deng, Xian-Hua Han, Yen-Wei Chen, Gang Xu, Yoshinobu Sato, Masatoshi Hori, Noriyuki Tomiyama:
Sparse and Low-Rank Matrix Decomposition for Local Morphological Analysis to Diagnose Cirrhosis. IEICE Trans. Inf. Syst. 97-D(12): 3210-3221 (2014) - 2013
- [j2]Amir Hossein Foruzan, Yen-Wei Chen, Reza Aghaeizadeh Zoroofi, Akira Furukawa, Yoshinobu Sato, Masatoshi Hori, Noriyuki Tomiyama:
Segmentation of Liver in Low-Contrast Images Using K-Means Clustering and Geodesic Active Contour Algorithms. IEICE Trans. Inf. Syst. 96-D(4): 798-807 (2013) - [c10]Yoshiyuki Kagiyama, Masaki Takao, Nobuhiko Sugano, Yukio Tada, Noriyuki Tomiyama, Yoshinobu Sato:
Optimization of surgical planning of total hip arthroplasty based on computational anatomy. EMBC 2013: 2980-2983 - [c9]Futoshi Yokota, Toshiyuki Okada, Masaki Takao, Nobuhiko Sugano, Yukio Tada, Noriyuki Tomiyama, Yoshinobu Sato:
Automated CT Segmentation of Diseased Hip Using Hierarchical and Conditional Statistical Shape Models. MICCAI (2) 2013: 190-197 - [c8]Dipti Prasad Mukherjee, Keisuke Higashiura, Toshiyuki Okada, Masatoshi Hori, Yen-Wei Chen, Noriyuki Tomiyama, Yoshinobu Sato:
Utilizing Disease-Specific Organ Shape Components for Disease Discrimination: Application to Discrimination of Chronic Liver Disease from CT Data. MICCAI (1) 2013: 235-242 - [c7]Toshiyuki Okada, Marius George Linguraru, Masatoshi Hori, Ronald M. Summers, Noriyuki Tomiyama, Yoshinobu Sato:
Abdominal Multi-organ CT Segmentation Using Organ Correlation Graph and Prediction-Based Shape and Location Priors. MICCAI (3) 2013: 275-282 - 2012
- [j1]Itaru Otomaru, Masahiko Nakamoto, Yoshiyuki Kagiyama, Masaki Takao, Nobuhiko Sugano, Noriyuki Tomiyama, Yukio Tada, Yoshinobu Sato:
Automated preoperative planning of femoral stem in total hip arthroplasty from 3D CT data: Atlas-based approach and comparative study. Medical Image Anal. 16(2): 415-426 (2012) - [c6]Toshiyuki Okada, Marius George Linguraru, Masatoshi Hori, Yuki Suzuki, Ronald M. Summers, Noriyuki Tomiyama, Yoshinobu Sato:
Multi-organ segmentation in abdominal CT images. EMBC 2012: 3986-3989 - [c5]Yuki Suzuki, Toshiyuki Okada, Masatoshi Hori, Futoshi Yokota, Marius George Linguraru, Noriyuki Tomiyama, Yoshinobu Sato:
Automated Segmentation and Anatomical Labeling of Abdominal Arteries Based on Multi-organ Segmentation from Contrast-Enhanced CT Data. CLIP 2012: 67-74 - 2011
- [c4]Toshiyuki Okada, Marius George Linguraru, Yasuhide Yoshida, Masatoshi Hori, Ronald M. Summers, Yen-Wei Chen, Noriyuki Tomiyama, Yoshinobu Sato:
Abdominal Multi-Organ Segmentation of CT Images Based on Hierarchical Spatial Modeling of Organ Interrelations. Abdominal Imaging 2011: 173-180
2000 – 2009
- 2003
- [c3]Shuji Yamamoto, Seiki Hamada, Takeshi Johkoh, Tomoo Inoue, Yasuhiro Tamaki, Sachiko Murai, Noriyuki Tomiyama, Kaname Tomoda, Hironobu Nakamura:
Three-dimensional image processing for breast cancer using multislice CT. CARS 2003: 1312 - 2001
- [c2]Kazuyoshi Hidaka, Yasuhiko Okura, Takeshi Johkoh, Seiki Hamada, Noriyuki Tomiyama, Osamu Honda, Takenori Kozuka, N. Mihara, Mitsuhiro Koyama, Mitsuko Tsubamoto, M. Maeda, Kiyonari Inamura, Hironobu Nakamura, Keiichi Fujiwara, H. Saki:
Time study of computer aided diagnosis - a preliminary results on temporal subtraction. CARS 2001: 599-604 - [c1]Takeshi Johkoh, Mitsuko Tsubamoto, Takenori Kozuka, Noriyuki Tomiyama, Seiki Hamada, Osamu Honda, Mitsuhiro Koyama, Hironobu Nakamura, Keiichi Fujiwara:
Temporal subtraction for the detection of ground-glass shadow on chest radiographs: evaluation of the first commercially available robustic computer-aided diagnostic system. CARS 2001: 1150-1151
Coauthor Index
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