A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Lung nodule diagnosis using 3D template matching
Computers in Biology and Medicine
A 3-dimensional sift descriptor and its application to action recognition
Proceedings of the 15th international conference on Multimedia
Lung Nodule Diagnosis from CT Images Using Fuzzy Logic
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 03
Lung nodule detection in low-dose and thin-slice computed tomography
Computers in Biology and Medicine
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
IEICE - Transactions on Information and Systems
Computers in Biology and Medicine
Methodology for automatic detection of lung nodules in computerized tomography images
Computer Methods and Programs in Biomedicine
Shape “Break-and-Repair” Strategy and Its Application to Automated Medical Image Segmentation
IEEE Transactions on Visualization and Computer Graphics
Automatic lung nodule detection using template matching
ADVIS'06 Proceedings of the 4th international conference on Advances in Information Systems
Information Sciences: an International Journal
Computer Methods and Programs in Biomedicine
Automatic detection of lung nodules in CT datasets based on stable 3D mass-spring models
Computers in Biology and Medicine
Lung tumor segmentation in PET images using graph cuts
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
A novel method for pulmonary embolism detection in CTA images
Computer Methods and Programs in Biomedicine
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Computer-aided detection (CAD) can help radiologists to detect pulmonary nodules at an early stage. In pulmonary nodule CAD systems, feature extraction is very important for describing the characteristics of nodule candidates. In this paper, we propose a novel three-dimensional shape-based feature descriptor to detect pulmonary nodules in CT scans. After lung volume segmentation, nodule candidates are detected using multi-scale dot enhancement filtering in the segmented lung volume. Next, we extract feature descriptors from the detected nodule candidates, and these are refined using an iterative wall elimination method. Finally, a support vector machine-based classifier is trained to classify nodules and non-nodules. The performance of the proposed system is evaluated on Lung Image Database Consortium data. The proposed method significantly reduces the number of false positives in nodule candidates. This method achieves 97.5% sensitivity, with only 6.76 false positives per scan.