The Hough Transform and the Impact of Chronic Leukemia on the Compact Bone Tissue from CT-Images Analysis

  • Anna Maria MassoneEmail author
  • Cristina Campi
  • Francesco Fiz
  • Mauro Carlo Beltrametti
Part of the Springer INdAM Series book series (SINDAMS, volume 36)


Computational analysis of X-ray Computed Tomography (CT) images allows the assessment of alteration of bone structure in adult patients with Advanced Chronic Lymphocytic Leukemia (ACLL), and may even offer a powerful tool to assess the development of the disease (prognostic potential). The crucial requirement for this kind of analysis is the application of a pattern recognition method able to accurately segment the intra-bone space in clinical CT images of the human skeleton. Our purpose is to show how this task can be accomplished by a procedure based on the use of the Hough transform technique for special families of algebraic curves. The dataset used for this study is composed of sixteen subjects including eight control subjects, one ACLL survivor, and seven ACLL victims. We apply the Hough transform approach to the set of CT images of appendicular bones for detecting the compact and trabecular bone contours by using ellipses, and we use the computed semi-axes values to infer information on bone alterations in the population affected by ACLL. The effectiveness of this method is proved against ground truth comparison. We show that features depending on the semi-axes values detect a statistically significant difference between the class of control subjects plus the ACLL survivor and the class of ACLL victims.


X-ray tomography Image processing Pattern recognition Hough transform Algebraic plane curves 



We acknowledge support from INDAM grant (intensive period on Computational Methods for Inverse Problems in Imaging). We wish to thank Gianmario Sambuceti, Head of the Nuclear Medicine Unit of the IRCCS San Martino - IST, Università degli Studi di Genova, and our colleague and friend Michele Piana for many helpful discussions. Special thanks should be given to Annalisa Perasso for her contribution to the data analysis of this project.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Anna Maria Massone
    • 1
    Email author
  • Cristina Campi
    • 2
  • Francesco Fiz
    • 3
  • Mauro Carlo Beltrametti
    • 1
  1. 1.Dipartimento di MatematicaUniversità di GenovaGenovaItaly
  2. 2.Dipartimento di MatematicaTullio Levi-Civita, Università di PadovaPadovaItaly
  3. 3.Nuclear Medicine Unit, Department of RadiologyUniversity of TuebingenTübingenGermany

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