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Coupling Deformable Models for Multi-object Segmentation

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Biomedical Simulation (ISBMS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5104))

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Abstract

For biomechanical simulations, the segmentation of multiple adjacent anatomical structures from medical image data is often required. If adjacent structures are hardly distinguishable in image data, automatic segmentation methods for single structures in general do not yield sufficiently accurate results. To improve segmentation accuracy in these cases, knowledge about adjacent structures must be exploited. Optimal graph searching based on deformable surface models allows for a simultaneous segmentation of multiple adjacent objects. However, this method requires a correspondence relation between vertices of adjacent surface meshes. Line segments, each containing two corresponding vertices, may then serve as shared displacement directions in the segmentation process. The problem is how to define suitable correspondences on arbitrary surfaces. In this paper we propose a scheme for constructing a correspondence relation in adjacent regions of two arbitrary surfaces. When applying the thus generated shared displacement directions in segmentation with deformable surfaces, overlap of the surfaces is guaranteed not to occur. We show correspondence relations for regions on a femoral head and acetabulum and other adjacent structures, as well as preliminary segmentation results obtained by a graph cut algorithm.

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Fernando Bello P. J. Eddie Edwards

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© 2008 Springer-Verlag Berlin Heidelberg

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Kainmueller, D., Lamecker, H., Zachow, S., Hege, HC. (2008). Coupling Deformable Models for Multi-object Segmentation. In: Bello, F., Edwards, P.J.E. (eds) Biomedical Simulation. ISBMS 2008. Lecture Notes in Computer Science, vol 5104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70521-5_8

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  • DOI: https://doi.org/10.1007/978-3-540-70521-5_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70520-8

  • Online ISBN: 978-3-540-70521-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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