New Algorithm for Fractal Dimension Estimation based on Texture Measurements: Application on Breast Tissue Characterization
| Autor: | Salim Loudjedi, Kamila Khemis, Mahammed Messadi, Sihem Amel Lazzouni, Abdelhafid Bessaid |
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| Rok vydání: | 2016 |
| Předmět: |
animal structures
Breast tissue Computer science 02 engineering and technology respiratory system Fractal dimension Fractal analysis 030218 nuclear medicine & medical imaging Gray level 03 medical and health sciences Box counting 0302 clinical medicine Fractal 0202 electrical engineering electronic engineering information engineering natural sciences 020201 artificial intelligence & image processing Triangular prism Algorithm Classifier (UML) circulatory and respiratory physiology |
| Zdroj: | International Journal of Image, Graphics and Signal Processing. 8:9-15 |
| ISSN: | 2074-9082 2074-9074 |
| DOI: | 10.5815/ijigsp.2016.04.02 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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