<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Robust Denoising of Low-Dose CT Images Using Convolutional Neural Networks"^^ . "X-ray computed tomography (CT) images are widely used in medical diagnosis. A drawback of X-ray CT imaging is that the X-rays are harmful with high-dose. Reducing the X-ray dose can reduce the risks but introduce noise and artifacts in the reconstructed image. This paper presents a method, called FD-VGG for denoising of low-dose CT images. FD-VGG estimates the normal-dose image from a low-dose image and, hence, reduces noise and artifacts. In FD-VGG the loss function is defined by the combination of the mean square error(MSE) and perception loss. FD-VGG was trained on a dataset of 226200 low-dose and normal dose image pairs from 6 patients and evaluated on 100 low-dose images from 2 other patients. The corresponding normal dose images of these testing low-dose images are considered as standard images for quantitative evaluation. Two metrics namely PSNR, SSIM were used for objective evaluation. The experimental results showed that the proposed FD-VGG network was able to denoise low-dose images efficiently, in comparison with two state-of-the-art methods."^^ . "2019-12-12" . . . . . . . . . . . . . . . . "Manh Ha"^^ . "Luu"^^ . "Manh Ha Luu"^^ . . "Dinh Hoan"^^ . "Trinh"^^ . "Dinh Hoan Trinh"^^ . . "Thanh Trung"^^ . "Nguyen"^^ . "Thanh Trung Nguyen"^^ . . "Linh Trung"^^ . "Nguyen"^^ . "Linh Trung Nguyen"^^ . . . . "2019 6th NAFOSTED Conference on Information and Computer Science (NICS)"^^ . . . . . "HTML Summary of #3867 \n\nRobust Denoising of Low-Dose CT Images Using Convolutional Neural Networks\n\n" . "text/html" . . . "Electronics and Computer Engineering"@en . .