Fractal analysis of elastographic images for automatic detection of diffuse diseases of salivary glands: preliminary results

Comput Math Methods Med. 2013:2013:347238. doi: 10.1155/2013/347238. Epub 2013 May 16.

Abstract

The geometry of some medical images of tissues, obtained by elastography and ultrasonography, is characterized in terms of complexity parameters such as the fractal dimension (FD). It is well known that in any image there are very subtle details that are not easily detectable by the human eye. However, in many cases like medical imaging diagnosis, these details are very important since they might contain some hidden information about the possible existence of certain pathological lesions like tissue degeneration, inflammation, or tumors. Therefore, an automatic method of analysis could be an expedient tool for physicians to give a faultless diagnosis. The fractal analysis is of great importance in relation to a quantitative evaluation of "real-time" elastography, a procedure considered to be operator dependent in the current clinical practice. Mathematical analysis reveals significant discrepancies among normal and pathological image patterns. The main objective of our work is to demonstrate the clinical utility of this procedure on an ultrasound image corresponding to a submandibular diffuse pathology.

Publication types

  • Case Reports

MeSH terms

  • Computational Biology
  • Diagnosis, Computer-Assisted / methods*
  • Diagnosis, Computer-Assisted / statistics & numerical data
  • Elasticity Imaging Techniques / methods*
  • Elasticity Imaging Techniques / statistics & numerical data
  • Female
  • Fractals
  • Humans
  • Image Interpretation, Computer-Assisted / methods*
  • Middle Aged
  • Salivary Gland Diseases / diagnostic imaging*
  • Sialadenitis / diagnostic imaging
  • Submandibular Gland Diseases / diagnostic imaging