A SURVEY ON EARLY DETECTION AND PREDICTION OF LUNG CANCER

Abstract

Lung cancer is the number one cause of cancer deaths in both men and women in the U.S. and worldwide. The earlier detection of lung cancer is a challenging problem due to structure of cancer cell, where most of the cells are overlapped each other. For early detection and treatment stages image processing technique are widely used and for prediction of lung cancer, identification of genetic as well as environmental factors are very important in developing novel method of lung cancer prevention. In various cancer tumours such as lung cancer the time factor is very important to discover the abnormality issue in target images. Prediction of lung cancer we consider significant pattern and their corresponding weight age and score using decision tree algorithm. Using the significant pattern tool for lung cancer prediction system will develop. In this proposed system we use Histogram Equalization is used for preprocessing of images and feature extraction processes and neural network classifier to check the state of patient whether it is normal or abnormal. If the lung cancer is successfully detected and predicted in its early stages will reduce many treatment options and also reduce risk of invasive surgery and increase survival rate. Therefore lung cancer detection and prediction system will propose which is easy, cost effective and time saving. This will produce promising result for detection and prediction of lung cancer. Therefore early detection and prediction of lung cancer should play a vital role in the diagnosis process and also increase the survival rate ofpatient.