Lung Tumor Detection and Classification

Lung cancer is a leading reason of death worldwide it refers to the uncontrolled growth of abnormal cells in the lung. If not treated, this growth can spread past the lung by procedure of metastasis into close-by tissue and different parts of the body. The image processing methods are used commonly in various medical areas for improving prior detection and treatment stages, in which the time span or elapse is very important to identify the disease in the patient as possible as fast, especially in many tumors. The proposed method uses first detection of lung mass tissue uses segmentation with filtering, morphological operation etc. Geometrical features Extraction technique is used for calculating statistical features. At last classification and prediction is done by using the geometrical features are merged with Machine Learning classifier. Results of the classification gives, whether the CT Image is a normal Image or cancerous.