COVID-19 Detection From X-ray Images Using Deep Learning
Our project aims to create a solution that can easily detect covid-19 in an automated way, especially when The need for auxiliary diagnostic tools has increased as there are no accurate automated toolkits available. So, we’re going to use Transfer Learning with advanced and popular architectures like VGG16, VGG19, ResNet50 and trying out SIAMESE with pre-trained weights on the popular ImageNet dataset. This implementation use Keras with a TensorFlow backend, and it will be performed Then adapted to our dataset which is full of X-ray images in Covid-19 and No_findings folders.
COVID-19 | NO-Findings |
---|---|
125 IMAGE | 500 IMAGE |
If you have taken a close look at the results section, we can say that:
So, we can see that our project is quite successful, and we have seen that from the height performances achieved. However, there is still much more rooms for improvement, especially if we take into account the quality and the size of our dataset.
Finally, our best model is integrated into an Android application called COVID19KIT the mobile app created can detect COVID-19 from X-ray images in the phone gallery or even by taking a photo of your X-ray directly that you have in your hands or on an electronic screen .
The screen below shows the reserved app activities for covid-19 detection: