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Lung cancer is known as one of the most difficult cancers to cure. In order to improve the recovery rate for lung cancer, detection and treatment at an early stage of growth is necessary. For the purpose, chest CT images obtained by helical CT scanner have drawn interest in the detection of suspicious regions. This paper present a method to improve the detection accuracy of the system that we have developed to detect candidates of lung cancer based on helical CT images. The basic improvement of the system is to enhance the difference of intensity surfaces between suspicious and normal regions by using surface curvatures such as the Gaussian and the mean curvatures. Experiments to show its feasibility of improving the detection accuracy are demonstrated by applying the method to the chest CT images.

Computer aided diagnosis system for lung cancer based on helical CT images