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Type: Conference paper
Title: From lung images to lung models: A review
Author: Lee, S.
Kouzani, A.
Hu, E.
Citation: IEEE International Joint Conference on Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence): pp.2377-2383
Publisher: IEEE
Publisher Place: Online
Issue Date: 2008
Series/Report no.: IEEE International Joint Conference on Neural Networks (IJCNN)
ISBN: 9781424418206
ISSN: 2161-4393
Conference Name: IEEE International Joint Conference on Neural Networks (2008 : Hong Kong)
Statement of
S. L. A. Lee, A. Z. Kouzani and E. J. Hu
Abstract: Automated 3D lung modeling involves analyzing 2D lung images and reconstructing a realistic 3D model of the lung. This paper presents a review of the existing works on automatic formation of 3D lung models from 2D lung images. A common framework for 3D lung modeling is proposed. It consists of eight components: image acquisition, image pre-processing, image segmentation, boundary creation, image recognition, image registration, 3D surface reconstruction, and 3D rendering and visualization. The algorithms used by the existing systems to implement these components are also reviewed.
Description: © Copyright 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/IJCNN.2008.4634128
Appears in Collections:Aurora harvest
Environment Institute publications
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