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Rule-based labeling of CT head image

  • Dubravko Ćosić
  • Sven Lončarić
Image and Signal Processing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1211)

Abstract

A rule-based approach to the labeling of computed tomography (CT) head images containing intracerebral brain hemorrhage (ICH) is presented in this paper. Fully automated segmentation of CT image is achieved by the method composed of two components: an unsupervised fuzzy clustering and a rule-based labeling. The unsupervised fuzzy clustering algorithm outlines the regions in the input CT head image. Extracted regions are spatially localized and have uniform brightness. Region features and region-neighborhood relations are used to create the knowledge base for the rule-based system. The rule-based system performs the labeling of the segmented regions into one of the following labels: background, skull, brain, ICH, and calcifications. The rules are determined from the a priori knowledge about the relations between the CT image regions and their characteristics. The method has been applied to a number of real CT head images and has shown satisfactory results.

Keywords

Adjacent Region Fuzzy Cluster Region Area Head Image Label Rule 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Dubravko Ćosić
    • 1
  • Sven Lončarić
    • 1
  1. 1.Department of Electronic Systems and Information Processing Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia

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