A study on lung nodule detection using neural networks

Abstract

In this study, the authors developed a method for disease detection using an artificial neural network and digital image processing of a chest radiograph. In a conventional physical examination radiologists check the chest image projected on a viewing box by a magnifying glass and determine what the disease is. The detection of disease on X-ray fluoroscopy images is tedious and time-consuming for humans. This lowers the efficiency for chest diagnosis as many mistakes by the radiologist are caused because of the need to detect micropathology from a film of small size. So, the authors propose a method to quickly find out what the object on a chest radiograph is. This method comprises the functions of image sampling, median filter, neural network image equalizer and neural network pattern recognition. The authors confirm that this method has improved the problems of conventional methods.