Feature Extraction of the Lesion in Mammogram Images Using Segmentation by Minimizing the Energy and Orthogonal Transformation Adaptive

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Abstract: Segmentation and classification of breast masses in mammography play a crucial role in Computer Aided Diagnosis system (CAD) . In this paper we propose an approach consisting of two methods. The first is the main stage in image processing which is the mammograms segmentation. This method is based on the theory of all levels and minimization of the energy of the active contour which enables the selection of regions of interest of the mammograms images. While the second method is based on the theory of adaptive orthogonal transformation that will calculate the informative characteristics of regions of interest of mammography images. The characteristics obtained by this computing method allow the increase of the diagnostic certainty. To illustrate the effectiveness of the method we present the results of experiments carried out on the basis of images MIAS mammograms.

WSEAS Transactions on Biology and Biomedicine, ISSN / E-ISSN: 1109-9518 / 2224-2902, Volume 11, 2014, Art. #12

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Khalid El Fahssi, Abdelali Elmoufidi, Abdenbi Abenaou, Said Jai-Andaloussi, Abderrahim Sekkaki, "Feature Extraction of the Lesion in Mammogram Images Using Segmentation by Minimizing the Energy and Orthogonal Transformation Adaptive," WSEAS Transactions on Biology and Biomedicine, vol. 11, pp. 88-95, 2014, DOI:
Khalid El Fahssi, Abdelali Elmoufidi, Abdenbi Abenaou, Said Jai-Andaloussi, Abderrahim Sekkaki. Feature Extraction of the Lesion in Mammogram Images Using Segmentation by Minimizing the Energy and Orthogonal Transformation Adaptive. WSEAS Transactions on Biology and Biomedicine. 2014;11:88-95.
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