Detection of Lung Cancer In CT Images Using Different Classification Techniques

Abstract

Cancer is one of the most deadly diseases that results in death. Lung cancer is the most common type of cancer and the main cause of death from cancer. Lung cancer survival rates are highly dependent on early identification and staging of the tumor. Image processing technique has a major role in the area of medical, in the detection of diseases. Computer Aided Diagnosis (CAD) systems were created to identify lung cancer in its early stages. This research aims to improve lung cancer identification performance in terms of accuracy, range and responsiveness. This work demonstrates a computerized method in detecting lung cancer using computed tomography images. The algorithm for the detection of lung cancer identification has steps such as image pre-processing, which is carried out by median filter, next is to obtain the region of interest using watershed segmentation and feature extraction. Then the SVM classifier and the KNN classifier are used in the detection of lung cancer.