Title :
A new computer-aided detection system for pulmonary nodules
Author :
Tartar, A. ; Kilic, N. ; Olgun, D.C. ; Akan, A.
Author_Institution :
Muhendislik Bilimleri Bolumu, Istanbul Univ., Avcılar, Turkey
Abstract :
Computer-aided detection (CAD) systems can help radiologists in early stage diagnosing of lung abnormalities. In this study, a new CAD system is presented by using wavelet transform for pulmonary nodule detection. Classification is performed by using kernels of support vector machines. Results are compared to similar works in the literature. Proposed CAD system results in 82.1% sensitivity.
Keywords :
image classification; lung; medical image processing; object detection; radiology; support vector machines; wavelet transforms; CAD system; computer-aided detection system; early stage diagnosis; image classification; lung abnormality; pulmonary nodule detection; radiology; support vector machine kernels; wavelet transform; Computed tomography; Design automation; Graphics; Kernel; Lungs; Medical diagnostic imaging; CAD system; Pulmonary nodule; pattern recognition; support vector machine; wavelet transform;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
DOI :
10.1109/SIU.2013.6531293
