Smart access development for classifying lung disease with chest x-ray images using deep learning

Tarunika Kumaraguru; P Abirami; K M Darshan; S P Angeline Kirubha; S Latha; P Muthu

doi:10.1016/j.matpr.2021.03.650

Smart access development for classifying lung disease with chest x-ray images using deep learning

Mater Today Proc. 2021:47:76-79. doi: 10.1016/j.matpr.2021.03.650. Epub 2021 Apr 16.

Authors

Tarunika Kumaraguru¹, P Abirami¹, K M Darshan¹, S P Angeline Kirubha¹, S Latha², P Muthu¹

Affiliations

¹ Department of Biomedical Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu 603203, India.
² Department Electronics and Communication Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu 603203, India.

Abstract

Recently the world has come across a pandemic disease known as covid-19. The presence of symptoms of covid-19 and pneumonia may be alike to other types of lung illnesses. So, because of this, it is difficult for the affected person or medical experts to identify the condition. Chest x-ray provides general orientation which can be an initial investigative study in the analysis of lung diseases. Information from retenogram studies help the finding of covid-19 and pneumonia affecting the lungs. We use a Convolution Neural Network (CNN) in Tensor Flow and Keras based covid-19, pneumonia classification. The best fit model of CNN is then deployed in the Django framework for providing a better user interface and predicting the output.

Keywords: Covid-19; Deep learning; Django framework; Keras; Pneumonia; TensorFlow.