Automatic Ischemic Stroke Segmentation Using Various Techniques

  • Andrius Usinskas
  • Erinija Pranckeviciene
  • Thomas Wittenberg
  • Peter Hastreiter
  • Bernd F. Tomandl
Part of the Advances in Soft Computing book series (AINSC, volume 19)


Different methods of automatic segmentation of human brain ischemic stroke area in the computerized tomography scans are compared. Experts-radiologists performed the evaluation of segmentation techniques. A methodology of qualitative evaluation of the investigated methods is proposed. The best viability showed histogram, gray level co-occurrence matrix, mean and standard deviation methods, and supervised artificial neural network technique.


Ischemic Stroke Artificial Neural Network Image Segmentation Gray Level Medical Image Analysis 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Andrius Usinskas
    • 1
  • Erinija Pranckeviciene
    • 2
  • Thomas Wittenberg
    • 3
  • Peter Hastreiter
    • 4
  • Bernd F. Tomandl
    • 4
  1. 1.Vilnius Gediminas Technical UniversityVilniusLithuania
  2. 2.Kaunas University of TechnologyKaunasLithuania
  3. 3.Fraunhofer Institute for Integrated Circuits-Applied ElectronicsErlangenGermany
  4. 4.Neurocenter at the Clinics of the University Erlangen-NurembergErlangenGermany

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