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Avoiding Mesh Folding in 3D Optimal Surface Segmentation

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Advances in Visual Computing (ISVC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6938))

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Abstract

The segmentation of 3D medical images is a challenging problem that benefits from incorporation of prior shape information. Optimal Surface Segmentation (OSS) has been introduced as a powerful and flexible framework that allows segmenting the surface of an object based on a rough initial prior with robustness against local minima. When applied to general 3D meshes, conventional search profiles constructed for the OSS may overlap resulting in defective segmentation results due to mesh folding. To avoid this problem, we propose to use the Gradient Vector Flow field to guide the construction of non-overlapping search profiles. As shown in our evaluation on segmenting lung surfaces, this effectively solves the mesh folding problem and decreases the average absolute surface distance error from 0.82±0.29 mm (mean±standard deviation) to 0.79±0.24 mm.

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Author information

Authors and Affiliations

  1. Deptartment of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, 52242, USA

    Christian Bauer, Shanhui Sun & Reinhard Beichel

  2. The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, 52242, USA

    Christian Bauer, Shanhui Sun & Reinhard Beichel

  3. Deptartment of Internal Medicine, The University of Iowa, Iowa City, IA, 52242, USA

    Reinhard Beichel

Authors
  1. Christian Bauer
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  2. Shanhui Sun
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  3. Reinhard Beichel
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Editor information

Editors and Affiliations

  1. University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, 94720, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, 89512, Reno, NV, USA

    Darko Koracin

  5. Department of Computer Science and Engineering, University of South Carolina, 29208, Columbia, SC, USA

    Song Wang

  6. HRL Laboratories, 3011 Malibu Canyon Road, 90265-4797, Malibu, CA, USA

    Kim Kyungnam

  7. Purdue University, 47907-2021, West Lafayette, IN, USA

    Bedrich Benes

  8. Sandia National Laboratory, 87185, Albuquerque, NM, USA

    Kenneth Moreland

  9. University of Louisiana, 70504, Lafayette, LA, USA

    Christoph Borst

  10. Adobe Systems Incorporated, San Francisco, CA, USA

    Stephen DiVerdi

  11. Polytechnic Institute of NYU, 11201, Brooklyn, NY, USA

    Chiang Yi-Jen

  12. Lawrence Livermore National Laboratory, 94551-0808, Livermore, CA, USA

    Jiang Ming

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© 2011 Springer-Verlag Berlin Heidelberg

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Bauer, C., Sun, S., Beichel, R. (2011). Avoiding Mesh Folding in 3D Optimal Surface Segmentation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24028-7_20

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  • DOI: https://doi.org/10.1007/978-3-642-24028-7_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24027-0

  • Online ISBN: 978-3-642-24028-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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