Work place: Biomedical Engineering laboratory, Tlemcen University, 13000, Algeria
E-mail: sa_lazzouni@yahoo.fr
Website:
Research Interests: Models of Computation, Image Processing, Computer Architecture and Organization
Biography
Mahammed MESSADI Associate Professor at the biomedical engineering Department of Tlemcen University, Algeria. He received his PhD degree in biomedical engineering from Tlemcen University in 2010. He also received an engineer degree in electronics in 2002 from the electronics Department of technology faculty. His research interests include, medical images pre-processing, images processing, images analysis, extraction of parameters, and classification methods.
By Kamila Khemis Sihem A. Lazzouni Mahammed Messadi Salim Loudjedi Bessaid Abdelhafid
DOI: https://doi.org/10.5815/ijigsp.2016.04.02, Pub. Date: 8 Apr. 2016
Fractal analysis is currently in full swing in particular in the medical field because of the fractal nature of natural phenomena (vascular system, nervous system, bones, breast tissue ...). For this, many algorithms for estimating the fractal dimension have emerged. Most of them are based on the principle of box counting. In this work we propose a new method for calculating fractal attributes based on contrast homogeneity and energy that have been extracted from gray level co-occurrence matrix. As application we are investigated in the characterization and classification of mammographic images with SuportVectorMachine classifier. We considered in particular images with tumor masses and architectural disorder to compare with normal ones. We calculate, for comparison the fractal dimension obtained by a reference method (triangular prism) and perform a classification similar to the previous. Results obtained with new algorithm are better than reference method (classification rate is 0.91 vs 0.65). Hence new fractal attributes are relevant.
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