Classification of lung cancer stages on CT scan images using image processing

Abstract

Lung cancer is the uncontrolled growth of abnormal cells that starts off in one or both images. People who smoke have the greatest risk of lung cancer. The overall 5 year survival rate for lung cancer combining all stages is roughly 15%. Early detection of lung cancer can increase the chance of survival among people. Lung cancer may be found by imaging tests such as chest computed tomography scan as it provides more detailed picture. To classify the stages of lung cancer, image processing technique is developed. In this work, new algorithm is developed using image processing technique to detect the cancer at early stage with more accuracy. Image processing involves the pre-processing, feature extraction and finally classification steps.