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IPMI
2005
Springer

Automated Detection of Small-Size Pulmonary Nodules Based on Helical CT Images

9 years 5 months ago
Automated Detection of Small-Size Pulmonary Nodules Based on Helical CT Images
Abstract. A computer-aided diagnosis (CAD) system to detect smallsize (from 2 mm to around 10 mm) pulmonary nodules in helical CT scans is developed. This system uses different schemes to locate juxtapleural nodules and non-pleural nodules. For juxtapleural nodules, morphological closing, thresholding and labeling are performed to obtain volumetric nodule candidates; gray level and geometric features are extracted and analyzed using a linear discriminant analysis (LDA) classifier. To locate non-pleural nodules, a discrete-time cellular neural network (DTCNN) uses local shape features which successfully capture the differences between nodules and non-nodules, especially vessels. The DTCNN was trained using genetic algorithm (GA). Testing on 17 cases with 3979 slice images showed the effectiveness of the proposed system, yielding sensitivity of 85.6% with 9.5 FPs/case (0.04 FPs/image). Moreover, the CAD system detected many nodules missed by human visual reading. This showed that the...
Xiangwei Zhang, Geoffrey McLennan, Eric A. Hoffman
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where IPMI
Authors Xiangwei Zhang, Geoffrey McLennan, Eric A. Hoffman, Milan Sonka
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