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Lung cancer is a common type of cancer that requires early diagnosis due to its often fatal consequences. Computer image processing techniques may be useful to increase the speed and accuracy of lung cancer detection. In order to process medical images, computerized tomography images usually are incorporated due to their high resolution and low noise level. In this paper, the application of Computer-Aided Detection systems for the diagnosis of lung cancer has been studied - including preprocessing and segmentation methods, and data analysis techniques. The main goal was to investigate the latest technology for the development of computational diagnostic tools, so as to assist with the acquisition, processing, and analysis of the medical imagery data. However, there are aspects that still require further attention, such as to increase the sensitivity, reduce false positives, and optimize the detection of each type of nodule, even for differing size and shape. Keywords: Computer-aided detection (CAD) systems, Lung nodule detection, Medical image processing, Computed tomography (CT)