Chest-X-Ray Covid-19 Detection using CNN & Transfer Learning

The new coronavirus (COVID-19), declared by the World Health Organization as a pandemic, has infected more than 1 million people and killed more than 50 thousand. An infection caused by COVID-19 can develop into pneumonia, which can be detected by a chest X-ray exam and should be treated appropriately.

In this work, we propose an automatic detection method for COVID-19 infection based on chest X-ray images. Dataset is collected from kaggle platform. The Dataset contain :

1. 536 X-ray images of patients diagnosed with coronavirus.
2. 668 X-ray images of healthy patients.
3. 619 X-ray images of patients diagnosed with viral.

Here we apply two model :

1. CNN Model
   • Accuracy : 95%

evalution_with_cnn

confusion_marix_with_cnn

2. Transfer Learning Approch using MobileNet algorithem with pre-trained Imagenet weights(convolutional neural networks (CNNs) trained on ImageNet, and adapt them to behave as feature extractors for the X-ray images)
   • Accuracy : 97%

evalution_with_Transfer_learning

confusion_matrix_with_Transfer_Learning