Lung Cancer Diagnosis Using Deep Learning: VGG-19

Abstract

Abstract: Lung cancer is classified histologically into small cell and non–small cell lung cancers. The most common symptoms of lung cancer are cough, dyspnoea, haemoptysis, and systemic symptoms such as weight loss and anorexia. High-risk patients who present with symptoms should undergo chest radiography. If a likely alternative diagnosis is not identified, computed tomography and possibly positron emission tomography should be performed. If suspicion for lung cancer is high, a diagnostic evaluation is warranted. The diagnostic evaluation has three simultaneous steps (tissue diagnosis, staging, and functional evaluation), all of which affect treatment planning and determination of prognosis. The main aim of this project is to find out the whether the person having lung cancer or not and having a chance of occurring Cancer in the future. We can done this process by using the CT(Computed Tomography) Scan Images of the lungs of affected Person. And it also identifies the given input CT Scan Image belongs to which person, which means that the image belongs to Normal person or it belongs to Cancer person or it belongs to the person who is having the chance of occurring cancer in the future, Which is also known as the PreMalignant Classification of images is done by using various CNN Algorithm