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Denoising on Low-Dose CT Image Using Deep CNN
Yuta Sadamatsu,Seiichi Murakami,Guangxu Li,Tohru Kamiya 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Computed Tomography (CT) scans are widely used in Japan, and they contribute to public health. On the other hand, there is also a risk of radiation exposure. To solve this problem, attempts are being made to reduce the radiation dose during imaging. However, reducing the radiation dose causes noise and degrades image quality. In this paper, we propose an image analysis method that efficiently removes noise by changing the activation function of Deep Convolutional Neural Network (Deep CNN). Experimental tests using full-body slice CT images of pigs and phantom CT images of lungs with Poisson noise show that the proposed method is helpful by comparing them with normal-dose CT images and evaluating image quality using peak signal-to-noise ratio (PSNR).