Nomura Yukihiro

ノムラユキヒロ | Nomura Yukihiro

Affiliation and department：
Other affiliations (1)：

The University of Tokyo Faculty of Medicine University Hospital

Research field (1)： Medical systems

Research theme for competitive and other funds (7)：

2023 - 2027 Development of LPRD diagnosis support system using artificial intelligence
2023 - 2026 Development of a BERT Fine-Tuning Model Specialized in Diagnosis.
2023 - 2026 Non-invasive quantitative evaluation of liver diseases using comprehensive biophysical properties database as basis for ultrasound pathology
2018 - 2021 Study for performance improvement of automated lesion detection system in medical images using weakly-labeled data
2015 - 2018 Dynamic performance improvement in computer-assisted detection system for diagnostic imaging by combined application of online learning and transfer learning

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Papers (79)：

Yukihiro Nomura, Shouhei Hanaoka, Naoto Hayashi, Takeharu Yoshikawa, Saori Koshino, Chiaki Sato, Momoko Tatsuta, Yuya Tanaka, Shintaro Kano, Moto Nakaya, et al. Performance changes due to differences among annotating radiologists for training data in computerized lesion detection. International Journal of Computer Assisted Radiology and Surgery. 2024
Takahiro Nakao, Soichiro Miki, Yuta Nakamura, Tomohiro Kikuchi, Yukihiro Nomura, Shouhei Hanaoka, Takeharu Yoshikawa, Osamu Abe. Capability of GPT-4V(ision) in the Japanese National Medical Licensing Examination: Evaluation Study. JMIR medical education. 2024. 10. e54393
Yukiko Kono, Keiichiro Miura, Hajime Kasai, Shoichi Ito, Mayumi Asahina, Masahiro Tanabe, Yukihiro Nomura, Toshiya Nakaguchi. Breath Measurement Method for Synchronized Reproduction of Biological Tones in an Augmented Reality Auscultation Training System. Sensors. 2024. 24. 5. 1626-1626
Tomomi Takenaga, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Hisaichi Shibata, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe. Development and evaluation of an integrated liver nodule diagnostic method by combining the liver segment division and lesion localization/classification models for enhanced focal liver lesion detection. Radiological physics and technology. 2024. 17. 1. 103-111
Md Ashraful Alam, Shouhei Hanaoka, Yukihiro Nomura, Tomohiro Kikuchi, Takahiro Nakao, Tomomi Takenaga, Naoto Hayashi, Takeharu Yoshikawa, Osamu Abe. Improved identification of tumors in 18F-FDG-PET examination by normalizing the standard uptake in the liver based on blood test data. International journal of computer assisted radiology and surgery. 2024. 19. 3. 581-590

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MISC (12)：

野村行弘. 【胸部の最新画像情報2022】肺癌画像診断におけるAI活用. 臨床放射線. 2022. 67. 1. 11-17
M Takahashi, T Takenaga, Y Nomura, S Hanaoka, M Nemoto, T Yoshikawa, N Hayashi, S Abe. A preliminary study on creating a ground-truth image for deep learning-based body fat segmentation in MRI using multi-atlas segmentation. International Journal of Computer Assisted Radiology and Surgery. 2020. 15. S1. 205-206
粟井和夫, 檜垣徹, 中村優子, 成田圭吾, 寺田大晃, 福本航, 坂根寛晃, 野村行弘. シリーズ新潮流 Vol.9-The Next Step of Imaging Technology 人工知能で医療は変わるのか-加速する医療分野のAI開発の現在と未来臨床におけるAI活用の現状と展望 1.画像診断支援のためのAIの活用. Innervision. 2018. 33. 7. 50-54
吉川健啓, 野村行弘, 佐藤一誠, 林直人, 花岡昇平, 三木聡一郎, 阿部修. Dynamic performance improvement in computer-assisted detection software for diagnostic imaging by combined application of online learning and transfer learning. 臨床放射線. 2017. 62. 10. 1237-1243
S. Miki, N. Hayashi, Y. Nomura, Y. Masutani. Time to check CAD results. American Journal of Neuroradiology. 2016. 37. 12. E81

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Lectures and oral presentations (139)：

医学物理における放射線科学の革新人工知能技術による放射線診断技術の革新
(日本放射線技術学会総会学術大会予稿集 2023)
深層学習を用いたUltra-short TE MR画像における肺野・気管支領域の自動抽出
(日本放射線技術学会総会学術大会予稿集 2023)
上部消化管内視鏡動画解析による自動診療報酬算定システムの開発
(Gastroenterological Endoscopy 2022)
マンモグラフィ画像のRadiomics特徴量の臨床データとの相関について
(日本医学放射線学会秋季臨床大会抄録集 2022)
差分プライバシーによる医用画像の匿名化と肺炎検出性能へ与える影響
(日本医学放射線学会秋季臨床大会抄録集 2022)

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Professional career (1)：

博士(工学) (千葉大学)

Work history (3)：

2021/07 - 現在 Chiba University
2019/05 - 2021/06 The University of Tokyo Faculty of Medicine University Hospital
2006/04 - 2019/04 The University of Tokyo Faculty of Medicine University Hospital

Awards (2)：

2020/05 - Japan Radiological Society JJR best paper award Can the spherical gold standards be used as an alternative to painted gold standards for the computerized detection of lesions using voxel-based classification?
2015/11 - 日本医用画像工学会 MIT誌論文賞遠隔読影環境における多施設連携型CAD開発、実運用、および継続的性能改善

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