Gooya, A. , Liao, H., Matsumiya, K., Masamune, K. and Dohi, T. (2007) Effective statistical edge integration using a flux maximizing scheme for volumetric vascular segmentation in MRA. In: Karssemeijer, N. and Lelieveldt, B. (eds.) Information Processing in Medical Imaging: 20th International Conference, IPMI 2007, Kerkrade, The Netherlands, July 2-6, 2007, Proceedings. Series: Lecture notes in computer science. Springer, pp. 86-97. ISBN 9783540732723 (doi: 10.1007/978-3-540-73273-0_8)
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Abstract
Evolutionary schemes based on the level set theory are effective tools for medical image segmentation. In this paper, a new variational technique for edge integration is presented. Region statistical measures and orientation information from ramp-like edges, are fused within an energy minimization scheme that is based on a new interpretation of edge concept. A region driven advection term simulating the edge strength effect is directly obtained from this minimization strategy. We have applied our method to several real Magnetic Resonance Angiography data sets and comparison has been made with a state-of-the-art vessel segmentation method. Presented results indicate that using this method a significant improvement is achievable and the method can be an effective tool to extract vessels in MRA intracranial images.
| Item Type: | Book Sections |
|---|---|
| Additional Information: | eISBN: 9783540732730. |
| Status: | Published |
| Glasgow Author(s) Enlighten ID: | Gooya, Dr Ali |
| Authors: | Gooya, A., Liao, H., Matsumiya, K., Masamune, K., and Dohi, T. |
| College/School: | College of Science and Engineering > School of Computing Science |
| Publisher: | Springer |
| ISBN: | 9783540732723 |
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