Detection of Lung Cancer using SVM Classifier

More number of deaths occurring every year due to a common health issue cancer. It is one of the diseases distributed over large area. Among all, lung cancer is most predominant having high death rate. Hence this is most important and a lot of research is going on and to identify lung cancer CT (Computed Tomography) scanned images are used. They provide a picture detailed with growth of tumor and tracks its growth in body so it is better by providing good results compared to other techniques. Therefore in medical fields most of the image processing techniques are used to detect the cancer in its early stages .In this paper we present an approach to detect lung cancer in scanned images. The steps involved in it is proposed using methods of image preprocessing where median filter is used followed by segmentation here mathematical morphological operations are used. Geometrical features like area, perimeter, and eccentricity are calculated to tumor detected part. At last SVM classifier is used to classify whether it is cancerous (Malignant) or normal (Benign).