Published June 1, 2021 | Version v1
Journal article

Classification of COVID 19 in Chest CT Images using Convolutional Neural Network

  • 1. Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai (India)

Description

The single-celled organisms called a virus are the root cause of many harmful diseases that affects both animals and humans. Coronavirus is one type of virus that is usually found in animals but if transmitted to humans can cause a wide range of respiratory diseases. One such disease caused is the COVID-19 diseases which caused a worldwide epidemic since its origin in 2019. The disease which is said to have originated in China had caused more than 252000 deaths worldwide in a few months. The test for the COVID-19 involves analysing the throat swab sample which may take days if not a week and by the time the results come the infection would have spread. Hence there is a need to improve the testing procedure for COVID-19. In this paper, we have come up with an automated Image Analysis technique to diagnose COVID-19 using the chest Computed Tomography images of the chest that uses a Convolutional Neural Network. This developed method has shown very good accuracy and efficiency in recognizing the COVID-19 infected CT images. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1742-6596/1917/1/012006

Additional details

Publishing Information

Journal Title
Journal of Physics. Conference Series (Online)
Journal Volume
1917
Journal Issue
1
Journal Page Range
[7 p.]
ISSN
1742-6596

Conference

Title
National Virtual Conference on Advanced Informatics, Electronics and Vision
Acronym
NCAIEV'21
Dates
23 Apr 2021
Place
Pollachi (India)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54005915
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE; S97: MATHEMATICAL METHODS AND COMPUTING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
CHEST; CLASSIFICATION; COMPUTERIZED TOMOGRAPHY; CORONAVIRUSES; DIAGNOSIS; EFFICIENCY; IMAGE PROCESSING; IMAGES; NEURAL NETWORKS; PHARYNX; TESTING
Descriptors DEC
BODY; DIAGNOSTIC TECHNIQUES; DIGESTIVE SYSTEM; DISEASES; INFECTIOUS DISEASES; MICROORGANISMS; ORGANS; PARASITES; PROCESSING; RESPIRATORY SYSTEM; TOMOGRAPHY; VIRAL DISEASES; VIRUSES; ZOONOTIC DISEASES