Detection of Lung Cancer using SVM Classifier and KNN Algorithm

In this computer era we are totally going with the automation of everything, in the same way the medical industry is also automated with the help of image processing and data analytics. The best way to control the death cause by cancer is early detection. The medical image or a CT scan image is pre-processed. The contrast of the image is increased with the CLAHE Equalization technique. Then it is segmented with the help of random walk segmentation method. In segmentation the three process will happen the ROI of image is segmented and then then the border correction is done. As third part the continuous pixel change is segmented. The classification is the major portion where the cancerous and non-cancerous is identified with the pre trained model. All the methods used above deals with the traditional way of image processing and data analytics. In Future this accuracy will be boosted with the modern XGboost algorithm where less data is used to get high accuracy.