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CT image segmentation by self-organizing learning

  • D. Cabello
  • M. G. Penedo
  • S. Barro
  • J. M. Pardo
  • J. Heras
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 686)

Abstract

In this paper we approach the segmentation of tibia CT images using a self-organizing feature map. This type of Artificial Neural Network carries out a competitive learning process which permits the discrimination of different structures found in the images with sensitivity to changes in the distribution and value of the gray levels of the pixels. The results obtained show that this technique is adequate for the segmentation of images with complex structures and a low signal/noise ratio.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • D. Cabello
    • 1
  • M. G. Penedo
    • 1
  • S. Barro
    • 1
  • J. M. Pardo
    • 1
  • J. Heras
    • 2
  1. 1.Departamento de Electrónica y Computación. Facultad de FísicaUniversidad de Santiago de CompostelaSpain
  2. 2.Servicio de Cirugía Ortopédica. Hospital General de GaliciaUniversidad de Santiago de CompostelaSpain

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