Title
: DETECTING COVID-19 CASES FROM RADIOLOGY (CHEST X-RAY) IMAGES USING DEEP LEARNING
Description
: COVID-19 or novel coronavirus which has been declared as a pandemic, at first had an outbreak in a small town of China, named Wuhan. Several countries of the world are already affected by this virus as it is spread by person-to-person interaction. The symptoms of this virus are quite similar to the general flu. There are few methods to detect COVID-19 which are performed on respiratory samples or blood samples. We propose a method to detect COVID-19 from the chest Xray image using the Convolutional Neural Network. From the results, the accuracy rate of the proposed to be quite high. The loss rate also decreases in the proposed method. Though this is not a clinically proven method, this proposed method might be of assistance while detecting COVID-19 presence in the human body.The most noticeable fact is that very few patients of COVID-19 associated Xray images, which leads to the scarcity of availability of Xray images. The more we get data from that open sources the more data will become available to update the dataset. The aim is to detect a patient COVID-19 affected or not using their chest Xray image. For the model building and training, we have used the Tensorflow library which is an open-source library for high-performance numerical computation. And we have used VGG-16 to train our model.
