Development of cellular neural network algorithm for detecting lung cancer symptoms

Abstract

Lung cancer is the most common of lethal types of cancer. One of the most important and difficult tasks a doctor has to carry out is the detection and diagnosis of cancerous lung nodules from x-ray image's result. Some of these lesions may not be detected because of camouflaged by the underlying anatomical structure, the low-quality of the images or the subjective and variable decision criteria used by doctors. Hence, a detection system using cellular neural network (CNN) is developed in order to help the doctors to recognize the doubtful lung cancer regions in x-ray films. In this study, a CNN algorithm for detecting the boundary and area of lung cancer in x-ray image has been proposed. Computer simulation result shows that our CNN algorithm is verified to detect some key lung cancer symptoms successfully and has been proved by radiologist.