Identification of Lung Cancer Using Backpropagation Neural Network

Abstract

Lung cancer is the most common cause of cancer-related human deaths in both men and women. Doing chest radiography is one of the first steps was investigated for lung cancer identification. In this study, theChest X-Ray imageswould be used as an input in pre-processing and continuing the feature extraction to be used in neural network process as a method proposed to identify lung cancer using backpropagation algorithm. Pre-processing is a first step to do some process such as scaling and greyscaling, the segmentation was K-means clustering process, then do the feature extraction usingGrey-Level Co-occurrence Matrix (GLCM) and identification using Backpropagation done by this study to identify the lung cancer. This study showed that the proposed method was able to identify the presence of cancer with an accuracy of 75%, sensitivity 75% and specificity of 75%.