@inproceedings{scholars872,
           pages = {73--76},
         address = {Kuala Lumpur},
           title = {Automatic detection of breast masses in digital mammograms using pattern matching},
         journal = {Proceedings of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010},
             doi = {10.1109/IECBES.2010.5742202},
            year = {2010},
            note = {cited By 5; Conference of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010 ; Conference Date: 30 November 2010 Through 2 December 2010; Conference Code:84636},
          author = {Eltoukhy, M. M. and Faye, I. and Samir, B. B.},
            isbn = {9781424476008},
        keywords = {Automatic Detection; Breast mass; Breast segmentation; Classification accuracy; Data sets; Digital mammograms; Mammographic image analysis; Mass detection; Mass regions; Region of interest extraction, Algorithms; Biomedical engineering; Image matching; X ray screens, Mammography},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955378402&doi=10.1109\%2fIECBES.2010.5742202&partnerID=40&md5=80657ef666b46584319f07f7040cb496},
        abstract = {The work in this paper focuses on the automatic detection of masses in digital mammograms. The proposed system consists of two main stages; the first stage is the breast segmentation to remove the background and labels. The second stage is to determine the masses region. The proposed method utilizes the correlation between a typical mass region and the mammogram image in order to determine and extract the suspicious region in the tested image. The system is developed and evaluated with 116 mammogram images from the mammographic image analysis society (MIAS) Dataset. The results show that the proposed algorithm has a sensitivity of 89.30 for mass detection, and the classification accuracy rate reach 94.66. {\^A}{\copyright} 2010 IEEE.}
}