Implementation of Machine Learning Techniques for detection of Lung Cancer

Abstract

An uncontrollable growth of body cells in lungs is called lung cancer. Lung cancer is ranked fourth among all the cancers over the world. Diagnosing of lung cancer is a vital step at early stages for increasing the survival rate. To detect lung cancer, CT (computed tomography) is an effective method to track lung cancer. In this proposed system, the software model is well -trained with different advanced CT images which are accurate and distinguished from the existing one. This proposed lung cancer model includes methods for segmenting the lung regions out of which GLCM parameters are collected and used for categorization of tumour stages using CNN. This proposed work has an efficiency of 98 percent.