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Removal of Pectoral Muscle Region in Digital Mammograms using Binary Thresholding

Removal of Pectoral Muscle Region in Digital Mammograms using Binary Thresholding

A. Kaja Mohideen, K. Thangavel
Copyright: © 2012 |Volume: 2 |Issue: 3 |Pages: 9
ISSN: 2155-6997|EISSN: 2155-6989|EISBN13: 9781466611276|DOI: 10.4018/ijcvip.2012070102
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MLA

Mohideen, A. Kaja, and K. Thangavel. "Removal of Pectoral Muscle Region in Digital Mammograms using Binary Thresholding." IJCVIP vol.2, no.3 2012: pp.21-29. http://doi.org/10.4018/ijcvip.2012070102

APA

Mohideen, A. K. & Thangavel, K. (2012). Removal of Pectoral Muscle Region in Digital Mammograms using Binary Thresholding. International Journal of Computer Vision and Image Processing (IJCVIP), 2(3), 21-29. http://doi.org/10.4018/ijcvip.2012070102

Chicago

Mohideen, A. Kaja, and K. Thangavel. "Removal of Pectoral Muscle Region in Digital Mammograms using Binary Thresholding," International Journal of Computer Vision and Image Processing (IJCVIP) 2, no.3: 21-29. http://doi.org/10.4018/ijcvip.2012070102

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Abstract

The pectoral muscle represents a predominant density region in Medio-Lateral Oblique (MLO) views of mammograms, which appears at approximately the same density as the dense tissues of interest in the image and can affect the results of image analysis methods. Therefore, segmentation of pectoral muscle is important in order to limit the search for the breast abnormalities only to the breast region. In this paper, a simple and effective approach is proposed to exclude the pectoral muscle based on binary operation. The performance is analyzed by the Hausdorff Distance Measure (HDM) and also the Mean of Absolute Error Distance Measure (MAEDM) based on differences between the results received from the radiologists and by the proposed method. The digital mammogram images are taken from MIAS dataset which contains 322 images in total, out of which the proposed algorithm able to detect and remove the pectoral region from 291 images successfully.

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