Rchr
J-GLOBAL ID：200901040057908971   Update date: Jan. 30, 2024

Mori Yasukuni

Mori Yasukuni
Affiliation and department：
Chiba University

About Chiba University


Research field  (5)： Medical systems ,  Biological, health, and medical informatics ,  Perceptual information processing ,  Statistical science ,  Intelligent informatics
Research keywords  (6)： Radiogenomics ,  Radiomics ,  Medical Imaging ,  Deep Learning ,  Feature Selection ,  統計的パターン認識
Research theme for competitive and other funds  (4)：
  • 2023 - 2026 高磁場MRリニアックによる時系列画像を用いたがんの超早期予後予測バイオマーカー確立
  • 2021 - 2024 がんのRadiogenomicsデータに対する深層学習による革新的特徴量選択
  • 2020 - 2023 AIとRadiogenomicsを応用した治療薬選択における癌不均一性の克服
  • 2017 - 2020 A Study on a High Dimensional Feature Selection Framework in the Big Data Era
Papers (15)：
  • Manami Takahashi, Reika Kosuda, Hiroyuki Takaoka, Hajime Yokota, Yasukuni Mori, Joji Ota, Takuro Horikoshi, Yasuhiko Tachibana, Hideki Kitahara, Masafumi Sugawara, et al. Deep learning-based coronary computed tomography analysis to predict functionally significant coronary artery stenosis. Heart and vessels. 2023. 38. 11. 1318-1328
  • Toshio Kumakiri, Shinichiro Mori, Yasukuni Mori, Ryusuke Hirai, Ayato Hashimoto, Yasuhiko Tachibana, Hiroki Suyari, Hitoshi Ishikawa. Real-time deep neural network-based automatic bowel gas segmentation on X-ray images for particle beam treatment. Physical and engineering sciences in medicine. 2023. 46. 2. 659-668
  • Katsuya Kosukegawa, Yasukuni Mori, Hiroki Suyari, Kazuhiko Kawamoto. Spatiotemporal forecasting of vertical track alignment with exogenous factors. Scientific reports. 2023. 13. 1. 2354-2354
  • Yosuke Iwatate, Hajime Yokota, Isamu Hoshino, Fumitaka Ishige, Naoki Kuwayama, Makiko Itami, Yasukuni Mori, Satoshi Chiba, Hidehito Arimitsu, Hiroo Yanagibashi, et al. Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived from transcriptome analysis in pancreatic cancer. International journal of oncology. 2022. 60. 5
  • Isamu Hoshino, Hajime Yokota, Yosuke Iwatate, Yasukuni Mori, Naoki Kuwayama, Fumitaka Ishige, Makiko Itami, Takashi Uno, Yuki Nakamura, Yasutoshi Tatsumi, et al. Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics. Cancer science. 2022. 113. 1. 229-239
ｍore...
MISC (30)：
  • KOSUKEGAWA Katsuya, KAWAMOTO Kazuhiko, MORI Yasukuni, SUYARI Hiroki. Spatio-temporal forecasting for railway track degradation detection with exogenous data. Proceedings of the Annual Conference of JSAI. 2022. JSAI2022. 4Yin224-4Yin224
  • 星野 敢, 森 康久仁, 岩立 陽祐, 石毛 文隆, 郡司 久, 桑山 直樹, 江藤 亮大郎, 外岡 亨, 早田 浩明, 滝口 伸浩, et al. Deep learningを用いた医学的情報の新たな解析の試み. 日本外科学会定期学術集会抄録集. 2021. 121回. SF-5
  • 田代弘平, 寺崎優希, 横田元, 太田丞二, 堀越琢郎, 森康久仁, 須鎗弘樹. False Positive Reduction Using Vascular Structure and Location Information for Cerebral Aneurysm Detection Model on MR Angiography. 人工知能学会全国大会論文集(Web). 2020. 34th
  • 小須田玲花, 小名木佑来, 太田丞二, 高橋愛, 高岡浩之, 堀越琢郎, 横田元, 森康久仁, 須鎗弘樹. Classification of Functionally Significant Coronary Artery Stenosis using LSTM. 人工知能学会全国大会論文集(Web). 2020. 34th
  • ONGGO Barata Tripramudya, OTA Joji, HORIKOSHI Takuro, YOKOTA Hajime, MORI Yasukuni, SUYARI Hiroki. Identifying the Corresponding CT Slices among the Different Scans via Deep Metric Learning. Proceedings of the Annual Conference of JSAI. 2020. 2020. 0. 2H5GS1305-2H5GS1305
ｍore...
Professional career (1)：
  • 博士 (北海道大学)
Association Membership(s) (2)：
IEEE ,  電子情報通信学会
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