Journal ArticleOpen Access
CovRoot: COVID-19 detection based on chest radiology imaging techniques using deep learning
Author Affiliations
BRAC University, Charles Sturt University, Victoria University
Published InFrontiers in Signal Processing
Year2024
Citations2
Abstract
The world first came to know the existence of COVID-19 (SARS-CoV-2) in December 2019. Initially, doctors struggled to diagnose the increasing number of patients due to less availability of testing kits. To help doctors primarily diagnose the virus, researchers around the world have come up with some radiology imaging techniques using the Convolutional Neural Network (CNN). Previously some research methods were based on X-ray images and others on CT scan images. Few research methods addressed both image types, with the proposed models limited to detecting only COVID and NORMAL cases. This limitation motivated us to propose a 42-layer CNN model that works for complex scenarios (COVID, NORMAL, and PNEUMONIA_VIRAL) and more complex scenarios (COVID, NORMAL, PNEUMONIA_VIRAL, and PNEUMONIA_BACTERIA). Furthermore, our…
View at Publisher
BORR does not host full-text PDFs. The button above takes you to the original publisher.