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ORCIDYuki Suzuki
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2020 – today
- 2024
[j3]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
- [c10]Kosuke Kita, Takahito Fujimori, Yuki Suzuki, Seiji Okada, Shoji Kido:
Bi-modal network combining convolutional neural network and TabNet, differentiating spinal tumors based on images and clinical risk factors. Computer-Aided Diagnosis 2023 - [c9]Keita Otani, Daiki Nishigaki, Taro Hatsutani, Takeshi Takamoto, Yuki Suzuki, Shoji Kido, Noriyuki Tomiyama:
Automatic characterization of liver tumors from multi-phase CT images. Computer-Aided Diagnosis 2023 - 2022
- [j2]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) - [c8]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 - [i4]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) - 2020
- [j1]Mitsuki Sakamoto, Yuta Hiasa, Yoshito Otake, Masaki Takao, Yuki Suzuki, Nobuhiko Sugano, Yoshinobu Sato:
Bayesian Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT Using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction. J. Signal Process. Syst. 92(3): 335-344 (2020) - [c7]Yuki Suzuki, Wataru Uemura:
A Novel Algorithm Checking for the Line Layout in a Factory. GCCE 2020: 617-619 - [c6]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. Computer-Aided Diagnosis 2020 - [i3]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
- [i2]Mitsuki Sakamoto, Yuta Hiasa, Yoshito Otake, Masaki Takao, Yuki Suzuki, Nobuhiko Sugano, Yoshinobu Sato:
Automated Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction. CoRR abs/1906.11484 (2019) - 2015
- [c5]Yuki Suzuki, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase:
Detector ensemble based on false positive mining for pedestrian detection. ACPR 2015: 745-749 - [c4]Yuki Suzuki, Takashi Yokota, Kanemitsu Ootsu, Takeshi Ohkawa:
Performance Improvement of Large-Scale Interconnection Network Simulator by Using GPU. CANDAR 2015: 585-589 - 2012
- [c3]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 - [c2]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
- [i1]Toshiki Endo, Yuki Suzuki:
Vertex unfoldings of tight polyhedra. CoRR abs/1109.0001 (2011)
2000 – 2009
- 2006
- [c1]Hidetomo Nabeshima, Reiko Miyagawa, Yuki Suzuki, Koji Iwanuma:
Rapid Synthesis of Domain-Specific Web Search Engines Based on Semi-Automatic Training-Example Generation. Web Intelligence 2006: 769-772
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