Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/56295
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Type: Conference paper
Title: Automated identification of lung nodules
Author: Lee, S.
Kouzani, A.
Hu, E.
Citation: MMSP 2008 : Proceedings of IEEE 10th International Workshop on Multimedia Signal Processing / D. Feng, T. Sikora, W.C. Siu, J. Zhang, L. Guan, J.-L. Dugelay, Q. Wu, W. Li (eds.): pp.497-502
Publisher: IEEE
Publisher Place: Online
Issue Date: 2008
ISBN: 9781424422944
Conference Name: IEEE Workshop on Multimedia Signal Processing (10th : 2008 : Cairns, Qld.)
Statement of
Responsibility: 
S. L. A. Lee, A. Z. Kouzani, and E. J. Hu
Abstract: A system that can automatically detect nodules within lung images may assist expert radiologists in interpreting the abnormal patterns as nodules in 2D CT lung images. A system is presented that can automatically identify nodules of various sizes within lung images. The pattern classification method is employed to develop the proposed system. A random forest ensemble classifier is formed consisting of many weak learners that can grow decision trees. The forest selects the decision that has the most votes. The developed system consists of two random forest classifiers connected in a series fashion. A subset of CT lung images from the LIDC database is employed. It consists of 5721 images to train and test the system. There are 411 images that contained expert- radiologists identified nodules. Training sets consisting of nodule, non-nodule, and false-detection patterns are constructed. A collection of test images are also built. The first classifier is developed to detect all nodules. The second classifier is developed to eliminate the false detections produced by the first classifier. According to the experimental results, a true positive rate of 100%, and false positive rate of 1.4 per lung image are achieved.
Description: ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
DOI: 10.1109/MMSP.2008.4665129
Appears in Collections:Aurora harvest
Environment Institute publications
Mechanical Engineering conference papers

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