eprintid: 3867
rev_number: 5
eprint_status: archive
userid: 366
dir: disk0/00/00/38/67
datestamp: 2019-12-19 03:17:44
lastmod: 2019-12-19 03:17:44
status_changed: 2019-12-19 03:17:44
type: conference_item
succeeds: 3661
metadata_visibility: show
creators_name: Nguyen, Thanh Trung
creators_name: Trinh, Dinh Hoan
creators_name: Nguyen, Linh Trung
creators_name: Luu, Manh Ha
creators_id: trungntktmt@gmail.com
creators_id: hoantd@gmail.com
creators_id: linhtrung@vnu.edu.vn
creators_id: halm@vnu.edu.vn
title: Robust Denoising of Low-Dose CT Images Using Convolutional Neural Networks
ispublished: inpress
subjects: ElectronicsandComputerEngineering
divisions: avitech
divisions: fac_fet
abstract: 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.
date: 2019-12-12
date_type: published
full_text_status: none
pres_type: paper
event_title: 2019 6th NAFOSTED Conference on Information and Computer Science (NICS)
event_type: conference
refereed: TRUE
citation:   Nguyen, Thanh Trung and Trinh, Dinh Hoan and Nguyen, Linh Trung and Luu, Manh Ha  (2019) Robust Denoising of Low-Dose CT Images Using Convolutional Neural Networks.  In: 2019 6th NAFOSTED Conference on Information and Computer Science (NICS).    (In Press)