Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 347238, 6 pages
Fractal Analysis of Elastographic Images for Automatic Detection of Diffuse Diseases of Salivary Glands: Preliminary Results
1Department of Cranio-Maxillo-Facial Surgery, University of Medicine and Pharmacy “Iuliu Haţieganu”, Cardinal Hossu Street 37, 400 029 Cluj-Napoca, Romania
2Department of Clinical Imaging, University of Medicine and Pharmacy “Iuliu Haţieganu”, Croitorilor Street 19-21, 400 162 Cluj-Napoca, Romania
3Department of Histology, Pasteur 5-6 University of Medicine and Pharmacy “Iuliu Haţieganu”, 400 349 Cluj-Napoca, Romania
4Department of Mathematics, University of Salerno, Via Ponte Don Melillo, 84084 Fisciano, Italy
5Department of Dental Prevention, University of Medicine Pharmacy “Iuliu Haţieganu”, Victor Babes Street, 400 012 Cluj-Napoca, Romania
6Department of System Biology, Phd School, University of Salerno, Via Ponte Don Melillo, 84084 Fisciano, Italy
7Department of Oral Health, University of Rome Tor Vergata, Viale Oxford, 00100 Rome, Italy
Received 10 March 2013; Accepted 12 April 2013
Academic Editor: Shengyong Chen
Copyright © 2013 Alexandru Florin Badea et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.