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최민혁(MinHyuk Choi),강세룡(SeRyong Kang),유지용(JiYong Yoo),양수(Su Yang),김다엘(Da-El Kim),김수정(SuJeong Kim),한지용(JiYong Han),임상헌(SangHeon Lim),송다현(Dahyun Song),김고은(Goeun Kim),용권순(KwonSoon Yong),이원진(WonJin Yi) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6
In dental imaging, Cone-beam computed tomography(CBCT) is widely used due to its high resolution, low radiation dose, and cost. However, motion artifact is a frequent issue due to difficulty in maintaining a stable posture during long scanning time. Therefore, we propose a method of reducing the motion artifact in CBCT imaging using D-Neural Radiance Fields(NeRF) generating a novel synthesized images in dynamic scenes. The experimental results indicate our model significantly outperforms other reconstruction tasks with three motion.