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Object-oriented volume segmentation

  • Biomedical Applications
  • Conference paper
  • First Online:
Computer Analysis of Images and Patterns (CAIP 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 719))

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Abstract

In this article we discuss three-dimensional image processing. Algorithms and data structures for this purpose are combined to form classes and objects in an object-oriented image analysis system. The major classes are volumes, octtrees, and image cubes. They provide reusable, problem-independent software components and hide implementation details. As an example, we show how data-driven volume segmentation of NMR-images can be accomplished using general assumptions about the image data. We point out how the classes can be integrated in an knowledge-based analysis system.

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References

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Authors and Affiliations

  1. Lehrstuhl für Mustererkennung (Informatik 5), Universität Erlangen-Nürnberg, Martensstraße 3, D-91058, Erlangen, FR of Germany

    Dietrich W. R. Paulus & Matthias Wolf

Authors
  1. Dietrich W. R. Paulus
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  2. Matthias Wolf
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Editor information

Dmitry Chetverikov Walter G. Kropatsch

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© 1993 Springer-Verlag Berlin Heidelberg

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Paulus, D.W.R., Wolf, M. (1993). Object-oriented volume segmentation. In: Chetverikov, D., Kropatsch, W.G. (eds) Computer Analysis of Images and Patterns. CAIP 1993. Lecture Notes in Computer Science, vol 719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57233-3_90

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  • DOI: https://doi.org/10.1007/3-540-57233-3_90

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57233-6

  • Online ISBN: 978-3-540-47980-2

  • eBook Packages: Springer Book Archive

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