GSA based classification of lung nodules in CT images

Medical Image processing techniques are widely used in several medical fields for earlier detection of diseases. CAD (Computer Aided Diagnostic) system yields a great deal of information to analyze and evaluate the accuracy of differential structures at short time period. Image quality with detailed edges is the core factors of this research, where low pre-processing technique is used for filtering. As a advanced method compared with standard median filter, the adaptive median filter performs spatial processing to preserve detail and smooth non-impulsive noise. Image segmentation is done using edge detection techniques in lung CT images for acquiring information, which is a prior step for feature extraction and selection. For detecting the differential structures a new edge detection algorithm is proposed, that is Gravitational search algorithm inspired by law of universal gravity. In this approach the edges are detected by the local variation of intensity values and the movement of agents is computed using Gravitational Search Algorithm (GSA).It gives fast and accurate framework for feature extraction and feature selection. For Feature Extraction Gray Level Co-occurrence Matrix