J-GLOBAL ID：201801001567983719
Update date: Mar. 24, 2024
Irie Ryusuke
Irie Ryusuke
Research field (1)：
Radiology
Research keywords (3)：
MRI
, Neuroradiology
, 放射線科学
Research theme for competitive and other funds (1)：
2021 - 2024 定量的マルチモーダルMRIを用いた自閉症スペクトラム障害の病態解明
Papers (56)：
Yuya Saito, Koji Kamagata, Christina Andica, Norihide Maikusa, Wataru Uchida, Kaito Takabayashi, Seina Yoshida, Akifumi Hagiwara, Shohei Fujita, Toshiaki Akashi, et al. Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping. Aging and disease. 2023
Takashi Arai, Koji Kamagata, Wataru Uchida, Christina Andica, Kaito Takabayashi, Yuya Saito, Rukeye Tuerxun, Zaimire Mahemuti, Yuichi Morita, Ryusuke Irie, et al. Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging. Frontiers in Neurology. 2023. 14
Ryusuke Irie, Shiori Amemiya, Tsuyoshi Ueyama, Yuichi Suzuki, Hidemasa Takao, Osamu Abe. Rapid MR Angiography Using 3D Gradient-echo Imaging and the Two-point Dixon Method to Evaluate Carotid Plaque. Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine. 2022. 22. 3. 373-378
FUJITA Shohei, OTSUKA Yujiro, HAGIWARA Akifumi, HORI Masaaki, TAKEI Naoyuki, HWANG Ken-Ping, IRIE Ryusuke, MAEKAWA Tomoko, ANDICA Christina, AKASHI Toshiaki, et al. Development of a Deep Learning Algorithm to Generate MR Angiography from 3D Quantitative Synthetic MR Imaging [Proceedings of the 2019 Young Investigator Award]. Japanese Journal of Magnetic Resonance in Medicine. 2022. 42. 1. 29-33
藤田翔平, 藤田翔平, 大塚裕次朗, 大塚裕次朗, 萩原彰文, 萩原彰文, 堀正明, 竹井直行, HWANG Ken-Ping, 入江隆介, et al. Development of a Deep Learning Algorithm to Generate MR Angiography from 3D Quantitative Synthetic MR Imaging [Proceedings of the 2019 Young Investigator Award]. 日本磁気共鳴医学会雑誌. 2022. 42. 1
Le Berre Alice, Le Berre Alice, Kamagata Koji, Otsuka Yujiro, Otsuka Yujiro, Andica Christina, Hatano Taku, Saccenti Laetitia, Saccenti Laetitia, Ogawa Takashi, et al. Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI. Neuroradiology (Web). 2019. 61. 12
