Yusuke Watanabe, Takuya Maeyama, Shinya Mizukami, Hidenobu Tachibana, Tsuyoshi Terazaki, Hideyuki Takei, Hiroshi Muraishi, Tsutomu Gomi, Shin-ichiro Hayashi. Verification of dose distribution in high dose-rate brachytherapy for cervical cancer using a normoxic N-vinylpyrrolidone polymer gel dosimeter. Journal of Radiation Research. 2022
Tsutomu Gomi, Yukie Kijima, Takayuki Kobayashi, Yukio Koibuchi. Evaluation of a Generative Adversarial Network to Improve Image Quality and Reduce Radiation-Dose during Digital Breast Tomosynthesis. Diagnostics. 2022. 12. 2. 495-495
K. Inoue, Y. Watanabe, T. Maeyama, S. Mizukami, S. Hayashi, T. Terazaki, H. Muraishi, T. Gomi, T. Shimono. RSC: Dosimetry in high-dose-rate brachytherapy with a radio-fluorogenic gel dosimeter. Journal of Physics: Conference Series. 2022. 2167. 1. 012032-012032
Shinya Mizukami, Yusuke Watanabe, Takahiro Mizoguchi, Tsutomu Gomi, Hidetake Hara, Hideyuki Takei, Nobuhisa Fukunishi, Kenichi Ishikawa, Shigekazu Fukuda, Takuya Maeyama. Whole Three-Dimensional Dosimetry of Carbon Ion Beams with an MRI-Based Nanocomposite Fricke Gel Dosimeter Using Rapid T1 Mapping Method. Gels. 2021. 7. 4
Tsutomu Gomi, Rina Sakai, Hidetake Hara, Yusuke Watanabe, Shinya Mizukami. Usefulness of a Metal Artifact Reduction Algorithm in Digital Tomosynthesis Using a Combination of Hybrid Generative Adversarial Networks. Diagnostics. 2021. 11. 9. 1629-1629
Okawa Akiko, Umeda Tokuo, Gomi Tsutomu. Development of a self-care support system for cancer outpatients undergoing radiotherapy: introduction of clinical path functions. The Kitasato medical journal. 2010. 40. 1. 64-72
Evaluation of unsupervised low-dose digital breast tomosynthesis denoising using cycle-consistent generative adversarial network
(RSNA 2023)
Usefulness of generative adversarial network-based low-dose digital breast tomosynthesis for image quality improvement
(RSNA 2022)
Development of a novel algorithm to improve image quality in chest digital tomosynthesis using convolutional neural network with super-resolution
(SPIE Medical Imaging 2021)
Development of a denoising convolutional neural network-based algorithm for metal artifact reduction in digital tomosynthesis
(SPIE Medical Imaging 2020)
Reduction of Metal Artifacts During Digital Tomosynthesis Reconstruction from Projection-Based Material Decomposition for Arthroplasty: A Phantom Study
(RSNA 2018)