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Erschienen in:
2012 | OriginalPaper | Buchkapitel
A Pulmonary Nodules Detection Method Using 3D Template Matching
verfasst von : Ting Gao, Xiwen Sun, Yuanjun Wang, Shengdong Nie
Erschienen in: Foundations of Intelligent Systems
Verlag: Springer Berlin Heidelberg
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A pulmonary nodules detection algorithm based on 3D template matching method using CT images is proposed. Firstly, lung parenchyma was segmented from CT series images. Secondly, apply the high-pass filter on the lung parenchyma images to enhance the edge of lung nodules. Then, design 3D templates with different size based on the nodules’ features. At last, apply the 3D-SSD (sum of squared differences) template matching algorithm between the 3D templates and the lung fields, and the final matching results were labeled as lung nodules on the original images. Using 20 clinical data set (include 35 pulmonary nodules in 3-20mm) to test the detection method, the accuracy rate is 81.08%, false positive rate (FP) is 5.4% and sensitivity rate is 85.71%. Therefore, the pulmonary nodules detection algorithm proposed in this paper can detect different typological nodules accurately and effectively.