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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.
적대적 신경망 기반 치과용 파노라마 영상의 방사선 선량 감소 방법
최민혁(MinHyuk Choi),강세룡(SaRyong Kang),유지용(Jiyong Yoo),최시은(Sieun Choi),전보성(Bosoung Jeoun),양수(Su Yang),천소영(Soyoung Chun),김진(Jin Kim),김다엘(DaEl Kim),이원진(Wonjin Yi) 대한전기학회 2021 대한전기학회 학술대회 논문집 Vol.2021 No.10
Dental panoramic radiography was widely used to screen the patient. Although the dose of panoramic radiography was lower than that of CT, it was higher than other medical imaging modality, such as intraoral x-ray and cephalometry. In this paper, we reconstructed the panoramic radiography from sparse view image using GAN for lower dose. Total 473 panoramic images were used to train the GAN model and test it. GAN could be reproduce the anatomy of teeth with 0.69±0.03 of structural similarity index.