Detection of lung cancer Using Artificial Neural Networks

Abstract

Lung cancer is considered to be the main cause of cancer death worldwide, and in its early stages it is difficult to detect because only in the advanced stage symptoms appear causing the mortality rate to be the highest among all other types of cancer. Lung cancer is cause due to uncontrolled growth of abnormal cells in one or both lungs, if it's missed with any treatment, this growth can be spread away from lung in a process called metastasis into nearby tissue of chest or other parts of the body The objective of this study is to design and develop an automated system for lung CT images diagnosis to Support the physicians‟ decisions in the diagnosis and treatment plan In this study, Data set of Lung CT images created by TCIA (The Cancer Imaging Archive) were used, MATLAB have been used through every procedures made on these images . In image processing procedures, process such as image preprocessing, then the features are extracted from the segmented lungs region using Haralick‟s feature, this step is followed by features selection and reduction to choose the best representative features. In the classification step Artificial Neural Network (ANN) was applied to classify images into normal or abnormal.