A novel computer-aided lung nodule detection system for CT images
Keywords:
Computer-aided diagnosis, Image features, Quantitative image feature analysis ,GA (Genetic Algorithm) , computed tomography (CT)Abstract
Lung cancer is a disease that occurs due to the uncontrolled cell growth in tissues of the lung. It is very
difficult to detect it in its early stages as its symptoms appear only in the advanced stages. The aim is to automate the
classification process for the early detection of Lung Cancer. It includes classification algorithm i.e. Neural Network and
for optimization GA (Genetic Algorithm) is used. Evaluation would be done on the basis of correctly classified sample
data. By using computed tomography (CT) images, a computer-aided detection scheme used to segment lung tumors and
computed tumor-related image features. All CT images were viewed at a computer workstation by one of four
investigative radiologists. Images were viewed at standard lung, soft tissue, and bone window settings. The steps for
detection of lung cancer starts with process of accepting CT Images. These CT images are further processed; using
training and testing methods features are classified using artificial neural network. This classification helps in evaluating
the results of the input CT image.
