東北大学 · 医学部 / 医学系研究科

研究关键词deep learning in radiotherapy・organ-at-risk dose prediction・cine MRI・radiomics・auto-segmentation・prostatic urethra

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• Multi-atlas-based auto-segmentation for prostatic urethra using novel prediction of deformable image registration accuracy.Hisamichi Takagi, Noriyuki Kadoya, Tomohiro Kajikawa, Shohei Tanaka, Yoshiki Takayama, Takahito Chiba, Kengo Ito, Suguru Dobashi, Ken Takeda, Keiichi Jingu
• Development of a prediction model for head and neck volume reduction by clinical factors, dose-volume histogram parameters and radiomics in head and neck cancer†.Miyu Ishizawa, Shohei Tanaka, Hisamichi Takagi, Noriyuki Kadoya, Kiyokazu Sato, Rei Umezawa, Keiichi Jingu, Ken Takeda
• Development and evaluation of deep learning models for estimating the organ at-risk dose constraint from two-dimensional cine magnetic resonance imaging scans during irradiation.Shohei Tanaka, Noriyuki Kadoya, Wingyi Lee, Hisamichi Takagi, Yoshiyuki Katsuta, Kazuhiro Arai, Yushan Xiao, Taichi Hoshino, Noriyoshi Takahashi, Keiichi Jingu
• Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy.Hisamichi Takagi, Ken Takeda, Noriyuki Kadoya, Koki Inoue, Shiki Endo, Noriyoshi Takahashi, Takaya Yamamoto, Rei Umezawa, Keiichi Jingu

• 体内に⼈⼯物を配置する密封⼩線源治療計画を⾃ 動かつ迅速に⾏う⼈⼯知能モデルの開発武田賢, 高城久道, 高橋季莉華, 田中祥平, 新井一弘, 勝田義之, 角谷倫之, 高橋紀善, 山本貴也, 梅澤玲, 神宮啓一
• 多因子深層学習モデルを用いた難治性尿路障害予測の検討高城 久道

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