LUNG CANCER DETECTION SYSTEM BY USING BAYESIAN CLASSIFIER

Medical image enhancement & classification play an important role in medical research area. To analyse the texture Computed Tomography (CT) images of lungs are taken to find the values of various parameters of texture. Mainly CT lung images are classified into normal and abnormal category. Classification of images depends on the features extracted from the images. Proposed system focusing on texture based features such as GLCM (Gray Level Cooccurrence Matrix) feature plays an important role in medical image analysis. Totally 12 different statistical features & 7 shape features will be extracted. To select the required features among them, use sequential forward selection algorithm. Afterwards prefer Bayesian classifier for the classification stage which gives perfect classification.