In this paper, we propose a novel algorithm to detect the suspicious regions on digital mammograms that based on the Fisher information measure. The proposed algorithm is tested different types and categories of mammograms (fatty, fatty-glandular and dense glandular) within mini-MIAS database (Mammogram Image Analysis Society database (UK)). The proposed method is compared with a different segmentation based information theoretical methods to demonstrate their effectiveness. The experimental results on mammography images showed the effectiveness in the detection of suspicious regions. This study can be a part of developing a computer-aided decision (CAD) system for early detection of breast cancer.
Abo-Eleneen, Z., & Abdel-Azim, G. (2013). A novel statistical approach for detection of suspicious regions in digital mammogram. Journal of the Egyptian Mathematical Society, 21(2), 162-168. doi: 10.1016/j.joems.2013.02.002
MLA
Z.A. Abo-Eleneen; Gamil Abdel-Azim. "A novel statistical approach for detection of suspicious regions in digital mammogram", Journal of the Egyptian Mathematical Society, 21, 2, 2013, 162-168. doi: 10.1016/j.joems.2013.02.002
HARVARD
Abo-Eleneen, Z., Abdel-Azim, G. (2013). 'A novel statistical approach for detection of suspicious regions in digital mammogram', Journal of the Egyptian Mathematical Society, 21(2), pp. 162-168. doi: 10.1016/j.joems.2013.02.002
VANCOUVER
Abo-Eleneen, Z., Abdel-Azim, G. A novel statistical approach for detection of suspicious regions in digital mammogram. Journal of the Egyptian Mathematical Society, 2013; 21(2): 162-168. doi: 10.1016/j.joems.2013.02.002
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