The work explained here and the source code presented here is accepted for publication at IEEE International Conference on Power Instrumentation Control and Computing (PICC 2020) and can be accessed from the given link.
This notebook will detect COVID-19 from Chest X-Ray images The year 2020 will certainly be remembered for the COVID-19 outbreak. First reported in Wuhan city of China back in December 2019, the number of people getting affected by this contagious virus has grown exponentially. Every country in this world been affected by this highly infectious disease.Shortage of testing kits and increasing number of fresh cases encouraged us to come up with a model that can aid radiologists in detecting COVID19 using chest X-ray images. With RT-PCR being the gold standard screening method and its time consuming nature, we aim to propose a real time model for detection of COVID19. Researchers all around the world are working day and night to counter this pandemic. Researchers of image processing and bio-medical engineering fields are also not left behind. Our ensemble model aims to classify the input Chest X-Ray into three classes namely- Community Acquired Pneumonia (CAP), Normal and COVID-19. Our ensemble model aims to classify the input Chest X-Ray into three classes namely- Community Acquired Pneumonia (CAP), Normal and COVID-19. Some of the examples are given in figure 1.
If you are using the code for your research work please cite our paper
Sagar Deep Deb and Rajib Kumar Jha, "COVID-19 detection from chest X-Ray images using ensemble of CNN models," 2020 International Conference on Power, Instrumentation, Control and Computing (PICC), Thrissur, India, 2020, pp. 1-5, doi: 10.1109/PICC51425.2020.9362499.
The dataset used for the experimentation is used from here.