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Computer-Aided Diagnosis system is used for diagnosing the lung cancer nodule from the chest Computer Tomography (CT) images. The System can automatically detect and diagnosis the lung cancer nodules with efficient accuracy and it also minimize the time taken by the radiologist for interpretation. The computer-aided diagnosis system is developed by combined techniques such as image denoising, segmentation, feature extraction and classification. CT lung image is denoised by the median filter. The system automatically segments region of interest from denoised lung computer tomography image using the proposed methodologies namely FSFCM. Then, the optimal initial cluster centres are created for the FSFCM to improve the segmentation results. This work presents a modified firefly search fuzzy C-means algorithm to produce efficient segmentation results.