Mammograms are the images used by radiologists to diagnose breast cancer. In this diagnosis, the pectoral muscle appears in mammograms in oblique mediolateral views (MLO) of the right breast and another in the left breast appears in cranio-caudal views which are marked with (CC). Considering that the pectoral muscle has the same density as the small, suspicious masses in the image, its presence in the image being processed could also require detection procedures. In this paper, we present a new general framework for pectoral muscle suppression which is the first work in the analysis of a mammography image. As a result, we proceed to four stages of image processing. The first step is to orient the image if necessary, then use a pre-processing which is to enhance the contrast of the image, and remove the digital lines of the image by morphological filters, apply a filter median. The third step involves segmenting all of the pectoral muscles, which involves threshold the entire image. The final step is to perform a pectoral muscle removal according to the orientation of the muscle in the image, which will be based on the development of the Hough transform for the recognition of borderline detections of the pectoral muscle. Some results obtained on the different images are discussed and compared with other methods (risk assessments). Evaluation of our method shows a significant improvement in performance in removing the pectoral muscle. Keywords: Breast cancer, Mammogram, Pectoral muscle, Hough transform.
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