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Computed Tomography (CT) is considered as the most sensitive imaging technique for early detection of lung cancer. On the other hand, there is a requirement for automated or semi-automated methodology in order to make use of large amount of data obtained from CT images and more accurately understanding of individual images. CAD can be used efficiently for early detection of lung cancer. Computer Aided Diagnosis (CAD) has been playing a significant role in cancer detection for the past two decades. Early detection of lung cancer is the only way by which the death rate can be reduced. But there is lot of difficulty in the early detection of lung cancer nodules. The usage of existing CAD systems for early detection of lung cancer with the help of CT images has been unsatisfactory because of its low sensitivity and high False Positive Rates (FPR).