Hindawi Publishing Corporation Computational and Mathematical Methods in Medicine Volume 2013, Article ID 347238, 6 pages http://dx.doi.org/10.1155/2013/347238 Research Article Fractal Analysis of Elastographic Images for Automatic Detection of Diffuse Diseases of Salivary Glands: Preliminary Results Alexandru Florin Badea, 1 Monica Lupsor Platon, 2 Maria Crisan, 3 Carlo Cattani, 4 Iulia Badea, 5 Gaetano Pierro, 6 Gianpaolo Sannino, 7 and Grigore Baciut 1 1 Department of Cranio-Maxillo-Facial Surgery, University of Medicine and Pharmacy “Iuliu Hat ¸ieganu”, Cardinal Hossu Street 37, 400 029 Cluj-Napoca, Romania 2 Department of Clinical Imaging, University of Medicine and Pharmacy “Iuliu Hat ¸ieganu”, Croitorilor Street 19-21, 400 162 Cluj-Napoca, Romania 3 Department of Histology, Pasteur 5-6 University of Medicine and Pharmacy “Iuliu Hat ¸ieganu”, 400 349 Cluj-Napoca, Romania 4 Department of Mathematics, University of Salerno, Via Ponte Don Melillo, 84084 Fisciano, Italy 5 Department of Dental Prevention, University of Medicine Pharmacy “Iuliu Hat ¸ieganu”, Victor Babes Street, 400 012 Cluj-Napoca, Romania 6 Department of System Biology, Phd School, University of Salerno, Via Ponte Don Melillo, 84084 Fisciano, Italy 7 Department of Oral Health, University of Rome Tor Vergata, Viale Oxford, 00100 Rome, Italy Correspondence should be addressed to Maria Crisan; mcrisan7@yahoo.com Received 10 March 2013; Accepted 12 April 2013 Academic Editor: Shengyong Chen Copyright © 2013 Alexandru Florin Badea et al. Tis 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. Te 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, infammation, or tumors. Terefore, an automatic method of analysis could be an expedient tool for physicians to give a faultless diagnosis. Te 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 signifcant discrepancies among normal and pathological image patterns. Te main objective of our work is to demonstrate the clinical utility of this procedure on an ultrasound image corresponding to a submandibular difuse pathology. 1. Introduction In some recent papers [1–4], the fractal nature of nucleotide distribution in DNA has been investigated in order to classify and compare DNA sequences and to single out some partic- ularities in the nucleotide distribution, sometimes in order to be used as markers for the existence of certain pathologies [5– 9]. Almost all these papers are motivated by the hypothesis that changes in the fractal dimension might be taken as markers for the existence of pathologies since it is universally accepted nowadays that bioactivity and the biological systems are based on some fractal nature organization [3, 4, 10–13]. From a mathematical point of view, this could be explained by the fact that the larger the number of interacting individuals, the more complex the corresponding system of interactions is. Tese hidden rules that lead to this complex fractal topology could be some simple recursive rules, typical of any fractal-like structure, which usually requires a large number of recursions in order to fll the space. In recent years, many papers [3–6, 9, 14, 15] have investigated the multi-fractality of biological signals such as DNA and the possible infuence of the fractal geometry on