Identification and prognosis of lung cancer by multi image optimization technique

Abstract

Air Pollution is responsible for many diseases and death happening all around newlinethe world. The PM ( Particulate Matter) present in the air is responsible for lung newlinediseases. The PM size is tiny and when the human inhales air, it directly reaches the newlinelungs and produces many diseases. An essential reason for air pollution is road newlinetransports. The vehicles produce a large amount of particulate matter. Lung Cancer is newlineone of the dangerous diseases created by PM in the air, and it is the third most deadly newlinedisease according to the American Cancer Society. newlineEarly prediction of lung cancer can be treated quickly, and there is an increase newlinein patients lifetime. However, it is complicated to foresee lung cancer at the premature newlinestage since many people will not find out the symptoms at early stages. Hence newlinedevelopment of CAD system and routine checkup will increase early prediction of newlinelung cancer. There are many CAD systems introduced globally, but due to newlinecomplexity, it is used in a few hospitals. newlineThe implementation of a CAD system in hospitals help radiologists to predict newlinethe cancer nodules that are smaller in size and also it acts as a second opinion for the newlinedoctors. The CAD system helps to save radiologists timing for detecting lung cancer. newlineThe proposed system consists of five steps: They are image acquisition to acquire newlineinput images from the user, image preprocessing to enhance the image so that newlineaccuracy will be introduced, image segmentation to find out the critical region and newlineeliminating other regions, feature extraction to extract the features of the critical newlineregion and classification to categorize the nodules as benign and malignant. newline