Rchr
J-GLOBAL ID：202001002511665301
Update date: May. 18, 2024
Hanaoka Shouhei
ハナオカ ショウヘイ | Hanaoka Shouhei
Affiliation and department：
Job title：
助教
Research theme for competitive and other funds (6)：
Papers (107)：
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Yuichiro Hirano, Shouhei Hanaoka, Takahiro Nakao, Soichiro Miki, Tomohiro Kikuchi, Yuta Nakamura, Yukihiro Nomura, Takeharu Yoshikawa, Osamu Abe. GPT-4 Turbo with Vision fails to outperform text-only GPT-4 Turbo in the Japan Diagnostic Radiology Board Examination. Japanese Journal of Radiology. 2024
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Tomohiro Kikuchi, Takahiro Nakao, Yuta Nakamura, Shouhei Hanaoka, Harushi Mori, Takeharu Yoshikawa. Towards Improved Radiological Diagnostics: Investigating the Utility and Limitations of GPT-3.5 Turbo and GPT-4 with Quiz Cases. American Journal of Neuroradiology. 2024. ajnr.A8332-ajnr.A8332
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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
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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
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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 (79)：
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中村優太, 花岡昇平, 花岡昇平, 野村行弘, 野村行弘, 片山僚, 小西池真緒, 越野沙織, 菊地智博, 中尾貴祐, et al. 深層学習による抽象型要約を用いた読影レポートimpressionの自動生成. 日本医学放射線学会秋季臨床大会抄録集. 2022. 58th
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野村行弘, 野村行弘, 花岡昇平, 花岡昇平, 林直人, 吉川健啓, 越野沙織, 佐藤千明, 龍田ももこ, 仲谷元, et al. CT画像の肺結節検出における再学習用正解データ入力者の違いによる性能変化に関する検討. 日本医学放射線学会秋季臨床大会抄録集. 2021. 57th
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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
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Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Naoto Hayashi, Osamu Abe. On the Matrix-Free Generation of Adversarial Perturbations for Black-Box Attacks. 2020
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H. Shibata, S. Hanaoka, Y. Nomura, T. Nakao, I. Sato, N. Hayashi, O. Abe. Anomaly detection in chest radiographs with a weakly supervised flow-based deep learning method. 2020
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Lectures and oral presentations (17)：
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脳動脈瘤検出ソフトウェアにおける病変候補の提示方法についての初期検討
(日本医学放射線学会秋季臨床大会抄録集 2019)
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胸部FDG-PETCT画像におけるdeep learningを用いた異常検知
(日本医学放射線学会秋季臨床大会抄録集 2018)
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Managing computer-assisted detection system based on transfer learning with negative transfer inhibition
(Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2018)
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Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition
(In Proceedings of 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2018) 2018)
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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)
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