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Fast Segmentation of Brain Magnetic Resonance Tomograms

  • Gangolf Mittelhäußer
  • Frithjof Kruggel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 905)

Abstract

We describe a combination of a region growing and a watershed algorithm optimized for the detection of homogeneous structures in magnetic resonance (MR) volume datasets. No prior knowledge is used except a segment model. The adaptation to different data sets is controlled by parameters which can be determined interactively due to the high speed of the algorithm. Results are shown for the segmentation of the basal ganglia and the white matter of the brain.

Keywords

White Matter Basal Ganglion Segment Model Gradient Magnitude Neighboring Segment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Upson C, Keeler M: “V-Buffer: Visible Volume Rendering”, Computer Graphics, Vol. 22, No. 4, Aug. 1988, pp. 59–64CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Gangolf Mittelhäußer
    • 1
  • Frithjof Kruggel
    • 2
  1. 1.University of KaiserslauternKaiserslauternGermany
  2. 2.Technical University MunichMunichGermany

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