A hybrid approach for classification of pulmonary lung nodules in ct images

Abstract

Cancer is a disease caused by an uncontrolled growth of abnormal cells in a part of the body.Lung cancer is the primary cause of cancer deaths in the two people. These abnormal cells grow rapidly and divide to form tumor in the lungs. The major cause of lung cancer is due to smoking and secondary cause is continuous exposure to air pollution, radon gas, and gene mutation. The survival rate is higher if the cancer is detected in early stages. Image processing plays a vital role in diagnostic test and helps to improve the survival rate of the patients. To detect lung cancer some automated and computerized system can be developed using image processing techniques. Computed Tomography (CT) scan is an important diagnostic tool used to diagnose cancer disease. Identifying and detecting cancerous lung cells from the CT images result is one of the most important and difficult tasks to be carried out by a doctor. Chemotherapy, radiation therapy and surgery are the treatments used for curing cancer. Lung cancer is diagnosed from the CT image of the lung. The Computer Aided Diagnosis (CAD) system is a significant tool which is used to diagnose the lung abnormalities in the early stage. Radiologists can use this CAD to detect accuracy and make the output as a second opinion to create the diagnostic choices. In recent years, image processing techniques have become more generally utilized. newline