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Region-Based Segmentation: Fuzzy Connectedness, Graph Cut and Related Algorithms

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Book cover Biomedical Image Processing

Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

Summary

In this chapter, we will review the current state of knowledge on regionbased digital image segmentation methods. More precisely, we will concentrate on the four families of such algorithms: (a) The leading theme here will be the framework of fuzzy connectedness (FC) methods. (b) We will also discuss in detail the family of graph cut (GC) methods and their relations to the FC family of algorithms. The GC methodology will be of special importance to our presentation, since we will emphasize the fact that the methods discussed here can be formalized in the language of graphs and GCs. The other two families of segmentation algorithms we will discuss consist of (c) watershed (WS) and (d) the region growing level set (LS) methods. Examples from medical image segmentation applications with different FC algorithms are also included.

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Author information

Authors and Affiliations

  1. Department of Mathematics, West Virginia University, Morgantown, WV, USA

    Krzysztof Chris Ciesielski

  2. Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA

    Krzysztof Chris Ciesielski & Jayaram K. Udupa

Authors
  1. Krzysztof Chris Ciesielski
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  2. Jayaram K. Udupa
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Corresponding author

Correspondence to Krzysztof Chris Ciesielski .

Editor information

Editors and Affiliations

  1. Inst. Medizinische Informatik, RWTH Aachen, Pauwelsstr. 30, Aachen, 52074, Germany

    Thomas Martin Deserno

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Ciesielski, K.C., Udupa, J.K. (2010). Region-Based Segmentation: Fuzzy Connectedness, Graph Cut and Related Algorithms. In: Deserno, T. (eds) Biomedical Image Processing. Biological and Medical Physics, Biomedical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15816-2_10

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  • DOI: https://doi.org/10.1007/978-3-642-15816-2_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15815-5

  • Online ISBN: 978-3-642-15816-2

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