Title :
Medical image texture segmentation using multifractal analysis
Author :
Korchiyne, Redouan ; Sbihi, Abderrahmane ; Farssi, Sidi Mohamed ; Touahni, Rajae ; Alaoui, Mustapha Tahiri
Author_Institution :
Lab. Syst. of Telecommun. & Eng. of Decision, Ibn Tofail Univ., Kenitra, Morocco
Abstract :
Medical image segmentation is a technique using to mean manually, fully or semi-automatically delineating the boundaries of tissue regions or an object. This paper presents a robust segmentation approach for medical image texture using multifractal analysis. The goal is to segment the images with respect to their characteristics such as bone and tissue types. In clinical situations where large numbers of data sets must be segmented, traditional methods may be tedious and biased. For these reasons, we used an automatic image segmentation algorithm, which eliminates the problem the classical method presents and expedites the process. In this paper, we present an algorithm to reliably segment medical images by using multifractal analysis. The result shows that the proposed method is able to analyze a broad range of medical images.
Keywords :
bone; fractals; image segmentation; image texture; medical image processing; automatic image segmentation algorithm; bone types; clinical situations; medical image segmentation; medical image texture segmentation; multifractal analysis; object tissue regions; tissue types; Algorithm design and analysis; Educational institutions; Feature extraction; Fractals; Image segmentation; Medical diagnostic imaging; Hausdorff spectrum; Multifractal analysis; fractal dimension; medical image; segmentation;
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2012 International Conference on
Conference_Location :
Tangier
Print_ISBN :
978-1-4673-1518-0
DOI :
10.1109/ICMCS.2012.6320316