Lung Cancer Detection Using Image Processing and Convolutional Neural Network

Abstract

Cancer is known to be one of the most dangeroushealth problems in the world and among it, lung cancer is knowntobethemostseriouscancerwiththesmallestsurvivalrate.Thelungcancerriskpopulationisalsoveryhighascomparedto other deadly diseases, for example, cardiovascular diseases.Therefore, early detection of lung cancer is a must for survival.Nowadays, a lot of research has been done using ConvolutionalNeural Networks in the medical field. Image classification is oneof the methods to detect cancer at early stages. First, the datasetsfor CT Scans are accessed from Kaggle. Images are refined withthe pre-processing method. The image dataset will be trained ontwo different models namely Manual CNN and AlexNet. Further,themodelproducingthehighestaccuracywillbechosenandtheprocessedimageswillbeusedtopredictwhethertheCTscan image is malignant (cancerous), benign (non-cancerous) ornormal.