Classification of healthy and affected lungs by pneumonia disease from x-ray images of lungs and gene sequencing using inception model

Hye-jin Kim

Kookmin University, Jeongneung-ro, Seongbuk-gu, Seoul, Korea

ABSTRACT

This project is entitled to predict the lung disease using chest x-rays by deep learning technique. Lung disease is a term that refers to improper functioning of lungs. There are many diseases which occur due to the abnormal functioning of lungs. It includes tuberculosis, pneumonia, lung cancer, asthma. The infection can be bacterial, viral or fungal. It causes inflammation of trachea and respiratory failure. If found earlier it can be cured else it can even lead to death. This project classifies the normal and abnormal x-ray with a percentage of accuracy so that we can give the treatment to the patient accordingly by seeing the x-ray. The algorithms used are Convolutional Neural Network (CNN) Inception Neural Network (INN) and Tensor Flow which is Google's open-source algorithm. The project is helpful for finding lung disease using chest x-ray.

Keywords:

Convolutional neural networks, Inspectional v3 model, Inspectional neural network, Trachea, Pneumonia, Bronchitis