Detection and Recognition of Lung Abnormalities Using Deformable Templates
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Computerized Detection of Pulmonary Nodule Based on Two-Dimensional PCA
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part II
Automated pulmonary nodule detection based on three-dimensional shape-based feature descriptor
Computer Methods and Programs in Biomedicine
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We have developed a computer-aided detection system for detecting lung nodules, which generally appear as circular areas of high opacity on serial-section CT images. Our method detected the regions of interest (ROIs) using the density values of pixels in CT images and scanning the pixels in 8 directions by using various thresholds. Then to reduce the number of ROIs the amounts of change in their locations based on the upper and the lower slices were examined, and finally a nodule template based algorithm was employed to categorize the ROIs according to their morphologies. To test the system's efficiency, we applied it to 276 normal and abnormal CT images of 12 patients with 153 nodules. The experimental results showed that using three templates with diameters 8, 14 and 20 pixels, the system achieved 91%, 94% and 95% sensitivities with 0.7, 0.98 and 1.17 false positives per image respectively.