Accurately and reliably automated segmentation of nodule could play an important role in lung cancer diagnosis. The chest Computer Tomography (CT) lung images are used to detect real malignant (cancerous) nodules. An effective Spatial Fuzzy C-means clustering with level set is proposed in this work to effectively segment the suspected lung nodules from CT images in order to detect the lung cancer. After segmentation, features were extracted and fed to neural network for classification. The classification process is done by using feed forward-back propagation in neural network. Performance of the proposed system was evaluated using 106 subjects? Computed Tomography (CT) images retrospectively obtained from the Bharat Scans, Chennai. The proposed method reduced the false positive nodule candidates significantly. It has achieved the sensitivity and accuracy of 88% and 84%, respectively.