Abstract
Breast area segmentation or skin-line extraction in mammograms is very important in many aspects. Prior segmentation can reduce the effects of background noise and artifacts on the analysis of mammograms. In this paper, we investigate a novel method to estimate the breast skin-line in mammograms. Adaptive thresholding [1] yields a nearly perfect skin-line at the center of the image and around the nipple area with images from the MIAS database [2], but the upper and lower portions of the extracted boundary have been observed to be erroneous due to noise and artifacts. Because the distance from the edge of the stroma to the actual skin-line is usually uniform, we propose a method to estimate the skin-line from the edge of the stroma, with the information provided by the center portion around the nipple from adaptive thresholding. The results are compared with the ground-truth boundaries drawn by a radiologist [3] using polyline distance measure and shape smoothness measure. The results on 83 mammograms from the MIAS database are demonstrated. The proposed methods led to a decrease in a shape smoothness measure based upon curvature, on the average, from 65.6 to 20.0 over the 83 mammograms tested, resulting in an improvement of 69.5%.
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Sun, Y., Suri, J., Rangayyan, R., Janer, R. (2005). Relationship Between the Stroma Edge and Skin-Air Boundary for Generating a Dependency Approach to Skin-Line Estimation in Screening Mammograms. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_82
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DOI: https://doi.org/10.1007/11552499_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28833-6
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