Journal ArticleOpen Access
Ensemble classification of integrated CT scan datasets in detecting COVID-19 using feature fusion from contourlet transform and CNN
Authors
Author Affiliations
Mawlana Bhashani Science and Technology University, University of York, Dhaka International University, Manchester Metropolitan University, ...
Published InScientific Reports
Year2023
Citations9
Abstract
The COVID-19 disease caused by coronavirus is constantly changing due to the emergence of different variants and thousands of people are dying every day worldwide. Early detection of this new form of pulmonary disease can reduce the mortality rate. In this paper, an automated method based on machine learning (ML) and deep learning (DL) has been developed to detect COVID-19 using computed tomography (CT) scan images extracted from three publicly available datasets (A total of 11,407 images; 7397 COVID-19 images and 4010 normal images). An unsupervised clustering approach that is a modified region-based clustering technique for segmenting COVID-19 CT scan image has been proposed. Furthermore, contourlet transform and convolution neural network (CNN) have been employed to extract features individually from…
View at Publisher
BORR does not host full-text PDFs. The button above takes you to the original publisher.