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Abnormal Textures Identification Based on Digital Hilbert Optics Methods: Fundamental Transforms and Models

  • Viktor Vlasenko
  • Sławomir Stemplewski
  • Piotr Koczur
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 656)

Abstract

The article presents the abnormal textures identification technology based on structural and statistical models of amplitude-phase images (APIm) – multidimensional data arrays (semantic models) and statistical correlation analysis methods using the generalized discrete Hilbert transforms (DHT) – 2D Hilbert (Foucault) isotropic (HTI), anisotropic (HTA) and total transforms – AP-analysis (APA) to calculate the APIm. The identified fragments of textures are obtained as examples of experimental observation of real mammograms contains areas of pathological tissues. The DHT based information technology as conceptual chart description is discussed and illustrated with DHO domain images. As additional method for anomaly of tissue detecting the multiply cascade DHT is proposed and elaborated at base transforms domains. The enhancement of abnormal texture areas at mammograms processed could increase the abilities of identification methodic and diagnostic systems.

Keywords

Generalized Hilbert transforms Amplitude-phase images Abnormal textures identification 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Viktor Vlasenko
    • 1
  • Sławomir Stemplewski
    • 2
  • Piotr Koczur
    • 1
  1. 1.Faculty of Nature and Technical SciencesOpole UniversityOpolePoland
  2. 2.Institute of Mathematics and Computer ScienceOpole UniversityOpolePoland

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