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Geometric Methods in Bio-Medical Image Processing pp 19–42Cite as

A Geometric Model for Image Analysis in Cytology

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Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

In this chapter, we propose a unified image analysis scheme for 3D computer assisted-cytology. The goal is to accurately extract and classify the shapes of nuclei and cells from confocal microscopy images. We make use of a geometry-driven scheme for preprocessing and analyzing confocal microscopy images. Namely, we build a chain of methods that includes an edge-preserving image smoothing mechanism, an automatic segmentation method, a geometry-driven scheme to regularize the shapes and improve edge fidelity, and an interactive method to split shape clusters and reclassify them. Finally we apply our scheme to segmenting nuclei using nuclear membrane and whole cells using cell-surface related proteins.

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Author information

Authors and Affiliations

  1. Lawrence Berkeley National Laboratory, University of California, Berkeley, CA, 94720, USA

    C. Ortiz de Solorzano & R. Malladi

  2. SAIC-Frederick, Frederick, MD, 21702, USA

    S. J. Lockett

Authors
  1. C. Ortiz de Solorzano
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  2. R. Malladi
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  3. S. J. Lockett
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Editor information

Editors and Affiliations

  1. 50A-1148 Lawrence Berkeley National Laboratory, University of California at Berkeley, 1, Cyclotron Rd., Berkeley, CA, 94720, USA

    Ravikanth Malladi

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© 2002 Springer-Verlag Berlin Heidelberg

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de Solorzano, C.O., Malladi, R., Lockett, S.J. (2002). A Geometric Model for Image Analysis in Cytology. In: Malladi, R. (eds) Geometric Methods in Bio-Medical Image Processing. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55987-7_2

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  • DOI: https://doi.org/10.1007/978-3-642-55987-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-62784-2

  • Online ISBN: 978-3-642-55987-7

  • eBook Packages: Springer Book Archive

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