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Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2024-03-04
09:00
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
Distance-informed adversarial learning for metal artifact reduction
Daisuke Shigemori, Megumi Nakao (Kyoto Univ.) MI2023-62
In this study, we propose an adversarial learning framework that utilises distance information from metal to reduce CT m... [more] MI2023-62
pp.95-98
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-20
16:00
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
Application of LambdaNetwork learning long-range interactions between pixels to metal artifact detection
Daisuke Shigemori, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-27 BioX2022-27 IE2022-27 MI2022-27
Although deep learning-based image transformation has been attempted to be applied to metal artifact reduction, feature ... [more] SIP2022-27 BioX2022-27 IE2022-27 MI2022-27
pp.138-143
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