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:: Volume 3, Number 4 (3-2017) ::
2017, 3(4): 300-309 Back to browse issues page
Designing a System for Detection of Pulmonary Nodules in Lung CT Images Using Support Vector Machine Classifier
Hamidreza Ghaffari, Mostafa Mosteshari , Maryam Sadat Mahmoodi
M.Sc. Computer Engineering, Department of Computer Engineering, Ferdows Branch, Islamic Azad University, Iran.
Abstract:   (298 Views)
Introduction: 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.
Methods: 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.
Results: 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.
Conclusion: According to the results of this study, the proposed system is more efficient than the previous methods for detecting suspicious nodules.
 
Keywords: Pulmonary Nodules, CT Scan Images, Support Vector Machine Classifier
Full-Text [PDF 1105 kb]   (107 Downloads)    
Type of Study: Original Article | Subject: Special
Received: 2016/12/18 | Accepted: 2017/03/11
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Ghaffari H, Mosteshari M, Mahmoodi M S. Designing a System for Detection of Pulmonary Nodules in Lung CT Images Using Support Vector Machine Classifier. Journal of Health and Biomedical Informatics. 2017; 3 (4) :300-309
URL: http://jhbmi.ir/article-1-166-en.html
Volume 3, Number 4 (3-2017) Back to browse issues page
مجله انفورماتیک سلامت و زیست پزشکی Journal of Health and Biomedical Informatics
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