Open AccessPneumonia Detection using Artificial Neural Networks and Transfer Learning Model
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1026.0782s419
Subject(s) - thresholding , pneumonia , transfer of learning , artificial intelligence , computer science , otsu's method , artificial neural network , pattern recognition (psychology) , task (project management) , deep learning , image (mathematics) , medicine , engineering , systems engineering
Developing a system that helps in detecting pneumonia in chest x-ray images of lungs at a high accuracy. Firstly, a raw image is being preprocessed with the help of Otsu Thresholding and an equalizer. This helps in detecting pneumonia clouds and identifying the ratio of healthy lung region to the total region minimum. The above task is determined by importing the original chest x-ray images in the dataset and then calculating the ratio. The preprocessed data is then fed into Inception V3 model that accurately predicts the percentage of how much pneumonia is spread. This helps in identifying pneumonia present in that area and helps determining the prescribed drugs to help them clear off the symptoms.