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| Lung CT Image Segmentation Based on Border Approximation |
| Huang Zhiding1 Sun Hong1,2,3* |
1 School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology, Shanghai 200093, China
2 Business School, University of Shanghai for Science and Technology, Shanghai 200093, China 3Shanghai Key Lab of Modern Optical System, Shanghai 200093, China |
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Abstract Segmentation of the lungs in chest-computed tomography (CT) image performs as an important preprocessing step in Computer-aided detection (CAD). The result brings a great effect for the further analysis and diagnosis. As the intensity of pleural nodule is close to the peripheral lung parenchyma, these lesions are not able to be segmented correctly using traditional method. The aim of this paper is to segment the lung including juxtapleural nodules in order to provide this focus for CAD system for the further analysis. This paper proposed a method that combined the Graham algorithm with border matching approximation to correct the contour of lung, and obtained the mask and multiply it by original image to segment lung image with juxtapleural nodules. Processing the 68 sample CT images including nodules from LIDC (Lung Image Database Consortium) through adopting new method proposed in this paper, and comparing this method with a traditional one, and analyzing the accuracy of this method and the rate of oversegmentation and undersegmentation, the accuracy of 98.5% , the oversegmentation rate of 1.35% and the undersegmentation of 0.51% were determined, which proved the effectiveness of this method.
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Received: 19 February 2016
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