Automated COVID-19 Detection

SARS-CoV-2

Severe Acute Respiratory Syndrome CoronaVirus 2.
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COVID-19

Coronavirus Disease 2019.
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Diagnostic Testing

Molecular Test, Rapid Antigen Test, Blood Test
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"Automated COVID-19 detection using Image Processing Techniques."

Background

Covid-19 is a highly infectious air borne disease which caused a lot of damage to life worldwide. One of the many challenges for containing the spread of COVID-19 is the ability to identify asymptomatic cases that result in spreading of the virus to close contacts.

Testing

Diagnostic tests can show if you suffer from an active COVID-19 infection and need to take steps to quarantine or isolate yourself from others. Antibody tests look for antibodies in your immune system produced in response to SARS-CoV-2, the virus that causes COVID-19.

Development

Recent studies revealed that Computed Tomography (CT) scan images can detect the COVID-19 disease in patients. This project is aimed to establish an early approach which is over-fitting independent and show accurate classification of CT-Scan images of lungs

Model

Automatic detection of COVID-19 based on DNN (Deep Neural Network) models are utilized in this work, along with the six distinct image processing models are applied on publicly available 402 COVID-19 infected and 397 normal images of lung CT-scan images.

About

This website has been made as a part of the course DSN-4099 Capstone Project 2021-22 by Team 8.

"Automated COVID-19 detection using Image Processing Techniques."

As a part of our Final Year Curriculum at VIT Bhopal University we the members of Team-8 have written a research paper titled "Automated COVID-19 detection using Image Processing Techniques." under the guidance of Dr.Anand Motwani Sir (Faculty SCSE VIT Bhopal) for the course Capstone Project (DSN-4099).

The DNN model is implemented for the automatic detection of various kinds of diseases and abnormalities in different image modalities. Automatic detection of COVID-19 based on DNN models are utilized in this work, along with the four distinct image processing models namely, convolution neural network, VGG-19, Inception, and Xception are applied on publicly available 402 COVID-19 infected and 397 normal images of lung CT-scan images.

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