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Research Article Open Access
Cancer is a serious health problem among various kinds of diseases. More than one in three people will be affected by some form of cancer during their lifetime. Among various types of cancer, Lung cancer is a leading cause of cancer-related death in many countries. The main aim is to find out the affected part i.e. uncontrolled growth and stage of disease in accurate manner by comparing two medical imaging techniques such as CT and PET scan. The scanned images may not have high resolution due to the number of slices per pixel and noise, so as an initial step need to preprocess the images using median filter which is used to remove the noise in an image. From the preprocessed images particular features will be selected using genetic algorithm and extracted using GLCM. The extracted images are classified using SVM classifier and stored, based on classification need to identify the stage of disease which is useful for the physician to give therapetical suggestions. The proposed System result shows the improved rate of early detection of lung cancer.
Genetic algorithm, GLCM, Lung cancer, SVM classifier., Lung Tumor,Lung Cancer Clinical Trials,Lung Cancer Immunotherapy,Cancer Signaling Array,Lung Cancer Prognosis,Lung Cancer Diagnosis