Automated Detection of Lung Cancer Using CT Scan Images

Lung cancer is one of the most threatening diseases among all other lung disorders which is caused for uncontrolled cell growth. The detection of lung cancer in early stages is the main comprehensible approach to enhance patient's survival rate. Image Processing together with machine learning process and other technologies are used to study medical images for earlier detection and treatment of present clinical world. This research study proposed an automated approach where Computed Tomography (CT) images are used to identify lung cancer at its early stage. The main objective of this research study is to achieve standard performance accuracy. We have proposed a new framework for lung cancer diagnosis using various features extracted from computed tomography images where different steps are used like enhancement, median, filter, segmentation, feature extraction and support vector machine. Finally, the experiment result shows the accuracy performance of our proposed method.