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Segmentation of Neural Stem/Progenitor Cells Nuclei within 3-D Neurospheres

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Advances in Visual Computing (ISVC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5875))

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Abstract

Neural stem cells derived from both embryonic and adult brain can be cultured as neurospheres; a free floating 3-D aggregate of cells. Neurospheres represent a heterogenous mix of cells including neural stem and progenitor cells. In order to investigate the self-renewal, growth and differentiation of cells within neurospheres, it is crucial that individual nuclei are accurately identified using image segmentation. Hence effective segmentation algorithm is indispensible for microscopy based neural stem cell studies. In this paper, we present a seed finding approach in scale space to identify the center of nuclei in 3-D. Then we present a novel segmentation approach, called “Evolving Generalized Voronoi Diagram”, which uses the identified centers to segment nuclei in neurospheres. Comparison of our computational results to mannually annotated ground truth demonstrates that the proposed approach is an efficient and accurate segmentation approach for 3-D neurospheres.

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Author information

Authors and Affiliations

  1. Bioinformatics Institute, #07-01, Matrix, 30 Biopolis Street, Singapore, 138671

    Weimiao Yu & Hwee Kuan Lee

  2. Institute of Medical Biology, #06-06, Immunos, 8A Biomedical Grove, Singapore, 138648

    Srivats Hariharan, Shvetha Sankaran & Sohail Ahmed

  3. CSIRO Mathematical and Information Sciences, Locked Bag 17, North Ryde, NSW, 1670, Australia

    Pascal Vallotton

Authors
  1. Weimiao Yu
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  2. Hwee Kuan Lee
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  3. Srivats Hariharan
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  4. Shvetha Sankaran
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  5. Pascal Vallotton
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  6. Sohail Ahmed
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

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

    Richard Boyle

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

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, Saitama, Japan

    Yoshinori Kuno

  6. Institute for Infocomm Research, 21 Heng Mui Keng Terrace, P.O. Box, 119613, Singapore

    Junxian Wang

  7. Department of Computer Science & Information Engineering, Tamkang University, Tamsui, Taipei, Taiwan, R.O.C.

    Jun-Xuan Wang

  8. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  9. Department of Informatics, Univ. of Zurich, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  10. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  11. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  12. Humana Inc., 40202, Louisville, KY, USA

    Miguel L. Encarnação

  13. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

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

    Daniel Coming

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© 2009 Springer-Verlag Berlin Heidelberg

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Yu, W., Lee, H.K., Hariharan, S., Sankaran, S., Vallotton, P., Ahmed, S. (2009). Segmentation of Neural Stem/Progenitor Cells Nuclei within 3-D Neurospheres. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10331-5_50

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  • DOI: https://doi.org/10.1007/978-3-642-10331-5_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10330-8

  • Online ISBN: 978-3-642-10331-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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