A Review of most Recent Lung Cancer Detection Techniques using Machine Learning

Lung cancer is a sort of dangerous cancer and difficult to detect. It usually causes death for both gender men & women therefore, so it is more necessary for care to immediately & correctly examine nodules. Accordingly, several techniques have been implemented to detect lung cancer in the early stages. In this paper a comparative analysis of different techniques based on machine learning for detection lung cancer have been presented. There have been too many methods developed in recent years to diagnose lung cancer, most of them utilizing CT scan images and some of them using x-ray images. In addition, multiple classifier methods are paired with numerous segmentation algorithms to use image recognition to identify lung cancer nodules. From this study it has been found that CT scan images are more suitable to have the accurate results. Therefore, mostly CT scan images are used for detection of cancer. Also, marker-controlled watershed segmentation provides more accurate results than other segmentation techniques. In Addition, the results that obtained from the methods based deep learning techniques achieved higher accuracy than the methods that have been implemented using classical machine learning techniques.