Identification of COVID-19 using X-Rays

This repository is an attempt to identify potentital COVID-19 cases using X-Rays as a decisive medium.

Architecture

The model is built on a custom CNN architecture (displayed below) with over 392 useful images in total from a dataset of over 1000+ X-Ray Images.

Project Execution

1. Open the Terminal.
2. Clone the repository by entering https://github.com/pranay-ar/Identification-of-COVID-19-Using-X-Rays.
3. Ensure that Python3 and pip/conda is installed on the system.
4. Create a virtualenv by executing the following command: virtualenv -p python3 env.
5. Activate the env virtual environment by executing the follwing command: source env/bin/activate.
6. Enter the cloned repository directory and execute pip install -r requirements.txt.
7. The entire code and the data extraction process can be found in the Jupyter Notebooks available in the repository

Performance Overview

Miscellaneous

The dataset has been acquired from Dr. Jospeh Paul Cohen's Github Repository link

COVID-19 Image Data Collection: Prospective Predictions Are the Future Joseph Paul Cohen and Paul Morrison and Lan Dao and Karsten Roth and Tim Q Duong and Marzyeh Ghassemi arXiv:2006.11988, https://github.com/ieee8023/covid-chestxray-dataset, 2020