Lung cancer is considered to be the main cause of cancer death worldwide and in its early stages it is difficult to detect because only in the advanced stage symptoms appear causing the mortality rate to be the highest among all other types of cancer. In this paper a study is presented in which an analysis is provided for the diagnosis and prediction of lung cancer at initial stage using Image Processing and Data Mining techniques. For detecting lung nodules number of tests should be required from the patient. But automated diagnosis system for prediction of lung cancer by using image processing and data mining techniques, plays an important role in time and performance which decreases mortality rate because of early detection of lung cancer. Different hybrid techniques provide different accuracy and sensitivity. This research paper analyzes various image processing and classification techniques and their efficiency.
Lung nodule, diagnosis, data mining, second most prevalent cancer in both men
