Lung cancer detection and nodule type classification using image processing and machine learning
Dorsaf Hrizi, Khaoula Tbarki, M. Attia, Sadok Elasmi
Abstract
Lung cancer is one of the most frequent type of cancers worldwide. It is a type of disease that grows out of control and forms abnormal cells in the lungs. These cells do not function like other normal cells due to deoxyribonucleic acid (DNA) mutation by various genetic factors. However, early detection and treatment of cases can reduce cancer-related mortality. In this paper we propose a novel system for cancer detection and classificaion based on image processing method and machine learning algorithms. Our system composed of two main process, the first is the preprocessing process to detect features and the second is the discrimination process to determine the type of lung cancer such as benign of malignant.