Designing a System for Detection of Pulmonary Nodules in Lung CT Images Using Support Vector Machine Classifier

Detection of pulmonary nodules using CT scan images is one of the methods for early detection of cancer. One of the main challenges for the detection of pulmonary nodules is identifying pulmonary nodules and differentiating them from lung components. In this study, a computer-aided detection system is proposed for the detection of these nodules.
In this descriptive analytical study, 97 chest CT-scan images were studied. To detect pulmonary nodules, support vector machine classifier and Genetic algorithm by MATLAB software were used.
In this research on the lung, the areas of images were classified into the two groups of with nodule and without nodule and it was tried to create a fully automated framework to detect lung nodules in the chest CT images. This framework is an essential part of the computer-aided detection system that helps radiologists to detect lung nodules more accurately and rapidly.
According to the results of this study, the proposed system is more efficient than the previous methods for detecting suspicious nodules.