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첨 단 인 공 지 능 기 술 을 통 해
Low-dose CT image denoising
The continuous development and extensive use of computed tomography (CT) in medical practice has raised a public concern over the associated radiation dose to the patient Reducing the radiation dose may lead to increased noise and artifacts, which can adversely affect the radiologists' judgment and confidence.
Detail- Revealing Deep Low-Dose CT Reconstruction
Low-dose CT imaging emerges with low radiation risk due to the reduction of radiation dose, but brings negative impact on the imaging quality. This paper addresses the problem of low-dose CT reconstruction.
인공지능 알고리즘 개발
PET/CT에 특화된 저화질의 영상을 고화질의 영상으로 복원시켜주는 고화질 영상 복원 응용 기술과 고선량의 고화질 영상이라 할 수 있는 chest CT 영상과 비슷한 수준에서 병변에 대한 판별을 가능하게 도와주는 판독 보조 인공지능 알고리즘 개발을 진행하였다.
생성적 적대 네트워크
This paper proposes a method of restoring corrupted depth image captured by depth camera through unsupervised learning using generative adversarial network (GAN). The proposed method generates restored face depth images using 3D morphable model convolutional neural network
