Gen Suzuki, Hideya Yamazaki, Norihiro Aibe, Koji Masui, Takuya Kimoto, Shinsuke Nagasawa, Kanako Kawabata, Tomohiro Kajikawa, Yuki Yoshino, Sho Seri, et al. Optimizing Therapeutic Approaches in Superficial Esophageal Cancer: Reduced-volume Radiotherapy and Dose-dense Chemotherapy After Endoscopic Resection. Anticancer research. 2024. 44. 7. 3133-3139
Ryota Tozuka, Noriyuki Kadoya, Seiji Tomori, Yuto Kimura, Tomohiro Kajikawa, Yuto Sugai, Yushan Xiao, Keiichi Jingu. Improvement of deep learning prediction model in patient-specific QA for VMAT with MLC leaf position map and patient's dose distribution. Journal of applied clinical medical physics. 2023. e14055
Yoshiyuki Katsuta, Noriyuki Kadoya, Tomohiro Kajikawa, Shina Mouri, Tomoki Kimura, Kazuya Takeda, Takaya Yamamoto, Nobuki Imano, Shohei Tanaka, Kengo Ito, et al. Radiation pneumonitis prediction model with integrating multiple dose-function features on 4DCT ventilation images. Physica Medica. 2023. 105. 102505-102505
Tomohiro Kajikawa, Noriyuki Kadoya, Yosuke Maehara, Hiroshi Miura, Yoshiyuki Katsuta, Shinsuke Nagasawa, Gen Suzuki, Hideya Yamazaki, Nagara Tamaki, Kei Yamada. A deep learning method for translating 3DCT to SPECT ventilation imaging: First comparison with 81mKr-gas SPECT ventilation imaging. Medical Physics. 2022. 49. 7. 4353-4364
Yoshiyuki Katsuta, Noriyuki Kadoya, Shina Mouri, Shohei Tanaka, Takayuki Kanai, Kazuya Takeda, Takaya Yamamoto, Kengo Ito, Tomohiro Kajikawa, Yujiro Nakajima, et al. Prediction of radiation pneumonitis with machine learning using 4D-CT based dose-function features. Journal of Radiation Research. 2021. 63. 1. 71-79
K Abe, N Kadoya, S Tanaka, Y Nakajima, S Hashimoto, T Kajikawa, K Karasawa, K Jingu. The Feasibility of MVCT-Based Radiomics for Delta-Radiomics in Head and Neck Cancer. Medical Physics. 2019. 46. 6. e142-e142
H Nemoto, N Kadoya, T Kajikawa, Y Nakajima, T Kanai, Y Ieko, K, Takeda, K Jingu. Evaluation of Factors That Affect 4D Cone Beam CT-Ventilation Images for Adaptive Functional Avoidance Radiotherapy. Medical Physics. 2019. 46. 6. e378-e378
A deep convolutional neural network approach for IMRT dose distribution prediction in prostate cancer patients
(The 18th Asia-Oceania Congress of Medical Physics (AOCMP) in conjunction with the 16th South-East Asia Congress of Medical Physics (SEACOMP))
A deep convolutional neural network approach for IMRT dose distribution prediction in prostate cancer patients
(AAPM 60th Annual Meeting)
2020/04 - 日本医学物理学会 MCA(Most Citation Award) Automated prediction of dosimetric eligibility of patients with prostate cancer undergoing intensity- modulated radiation therapy using a convolutional neural network.
