Fast and adaptive detection of pulmonary nodules in thoracic CT images based on improved fuzzy c-means medical image segmentation and SVM classifier

Lung cancer found to be the common cause of death among people all around the world.The chance of survival among people was increased with the early detection of lung cancer.There has been an increase in the survival rate from 14 to 40% when it is detected in its earlier stage.Computed Tomography (CT) can be more efficient than X-ray.To classify the present of lung cancer in an CT-images,a lung cancer detection system using image processing is used.In this method, MATLAB is used as the software tool for processing images.In image processing procedures, process such as image pre-processing, segmentation with procedure called as fuzzy cmeans(FCM) clustering and feature extraction with the help of GLCM matrix and classification by using ANN classifier have been performed.It is intended to get the more accurate results by using various enhancement and segmentation techniques.