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Norimitsu Shinohara

Showing results (11-20 of 18) with videos related to

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Medicine|July 8, 2020
A deep learning-based automated diagnostic system for classifying mammographic lesionsTakeshi Yamaguchi, Kenichi Inoue, Hiroko Tsunoda, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|January 22, 2019
[Selection of Radiomic Features for the Classification of Triple-negative Breast Cancer Based on Radiogenomics]Chiharu Kai, Mako Ishimaru, Yoshikazu Uchiyama, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|January 11, 2003
[A comparison between physicians' interpretation and a CAD system's cancer detection by using a mammogram database in a physicians' self-learning course]Yuji Hatanaka, Tomoko Matsubara, Takeshi Hara, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|August 20, 2023
[Trends and Future Prospects of AI Technology Utilization Research in JSRT　 -Challenges to Tackle and the Expected Role of Our Academic Society !?]Ikuo Kawashita, Norio Hayashi, Masahide Tominaga, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|September 18, 2023
[Digital Breast Tomosynthesis Quality Control Manual Overview]Norimitsu Shinohara, Shinobu Akiyama, Takahiro Ito, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|May 20, 2021
[Examination of the Quality Control Items for Digital Breast Tomosynthesis System in Japan]Norimitsu Shinohara, Shinobu Akiyama, Takahiro Ito, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|January 22, 2023
[Mission and Future Prospects of the Scientific Division]Norimitsu Shinohara, Takashi Iimori, Daisaku Tatsumi, et al.
Breast Cancer (Tokyo, Japan)|July 3, 2025
Development of a deep learning-based automated diagnostic system (DLADS) for classifying mammographic lesions - a first large-scale multi-institutional clinical trial in JapanTakeshi Yamaguchi, Yoichi Koyama, Kenichi Inoue, et al.
Pageof 2

Showing results (11-20 of 18) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 18 results.
Medicine|July 8, 2020
A deep learning-based automated diagnostic system for classifying mammographic lesionsTakeshi Yamaguchi, Kenichi Inoue, Hiroko Tsunoda, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|January 22, 2019
[Selection of Radiomic Features for the Classification of Triple-negative Breast Cancer Based on Radiogenomics]Chiharu Kai, Mako Ishimaru, Yoshikazu Uchiyama, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|January 11, 2003
[A comparison between physicians' interpretation and a CAD system's cancer detection by using a mammogram database in a physicians' self-learning course]Yuji Hatanaka, Tomoko Matsubara, Takeshi Hara, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|August 20, 2023
[Trends and Future Prospects of AI Technology Utilization Research in JSRT　 -Challenges to Tackle and the Expected Role of Our Academic Society !?]Ikuo Kawashita, Norio Hayashi, Masahide Tominaga, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|September 18, 2023
[Digital Breast Tomosynthesis Quality Control Manual Overview]Norimitsu Shinohara, Shinobu Akiyama, Takahiro Ito, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|May 20, 2021
[Examination of the Quality Control Items for Digital Breast Tomosynthesis System in Japan]Norimitsu Shinohara, Shinobu Akiyama, Takahiro Ito, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi|January 22, 2023
[Mission and Future Prospects of the Scientific Division]Norimitsu Shinohara, Takashi Iimori, Daisaku Tatsumi, et al.
Breast Cancer (Tokyo, Japan)|July 3, 2025
Development of a deep learning-based automated diagnostic system (DLADS) for classifying mammographic lesions - a first large-scale multi-institutional clinical trial in JapanTakeshi Yamaguchi, Yoichi Koyama, Kenichi Inoue, et al.
Pageof 2