Predictive Model for Lung Cancer Detection

Abstract

Lung cancer is the result of cells that develop widely in one or both of the lungs. Lung cancer is diagnosed in two ways non-small cell lung cancer and small cell lung cancer. Too late, lung cancer has been the main cause of death worldwide. If detected successfully in the early stages lung cancer allows for many treatment options, decrease the risk of aggressive surgery an increased rate of survival. So the early diagnosis of lung cancer is very important. Our aims and objectives to develop this system is to detect the lung cancer in an input image and shows that image of lung is normal or abnor0mal. Here we proposed a system where radiologist login with system by entering his/her email and password. Radiologist fill patient form with coordination of patient and upload CT scan image of lungs in predictive model for lung cancer detection and get output and print report .Several image processing techniques that we have used to design this system, Image Pre-processing, Image Segmentation, Image Filtering, Dilation, Image Filling, Feature Extraction Neural Network and Neuro Fuzzy classification algorithm is used for image classification. MATLAB is used to designed detection part of system.