Classification and Segmentation Techniques for Detection of Lung Cancer from CT Images

Information Technology(IT) has played an important role in all aspects of human life. In the recent years, it has influenced the medical and healthcare field. Image processing together with machine learning and other technologies are used to study medical images for earlier disease detection and treatment. Diseases like cancer should be discovered as fast as possible where time factor is vital. Medical images have factors such as noise, uncertain tumor boundaries and large variation in tumor appearance which makes it difficult to find exact tumor region. To overcome these problems, several methods are available for helping the radiologist in accurately detecting the cancer. This paper has reviewed classification and segmentation techniques used in detecting the lung cancer tumor and evaluated the performance of each approach. It has proposed a method for effective identification of lung cancer. The proposed method gave 79.166% accuracy.