Abdelali Elmoufidi

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This paper presents a method for the detection of the regions of interest's (ROIs) in mammograms by using dynamic k-means clustering algorithm. In this approach, a method has been developed to determine the initialization number of clusters in mammograms by using a data mining algorithm based on the Local Binary Pattern (LBP) and co-occurrence matrix(More)
Breast cancer is a leading cause of cancer type for death among women in most of popular countries, breast cancer detection is important and challenging role in worldwide to save women’s life. Due to inexperience to detect cancer, the doctors and radio logistic can miss the abnormality, which leads to death. Mammography is the most used method for breast(More)
Breast mass segmentation in mammography plays a crucial role in Computer-Aided Diagnosis (CAD) systems. We propose in this work a method for the segmentation of mammography images by using a combination of two approaches: one based on levels set theory and the other based on the principle of the minimization of the energy of active contours. The elaborated(More)
Breast cancer is the most common cancer and the leading cause of morbidity and mortality among women’s age between 50 and 74 years across the worldwide. In this paper we’ve proposed a method to detect the suspicious lesions in mammograms, extracting their features and classify them as Normal or Abnormal and Benign or Malignant for diagnosing of breast(More)
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