Most of the invisible nipples were caused by their nearly flat profiles, by the noise along the breast boundary, or by masking of the nipple behind dense tissue due to improper positioning. For the nipples that were projected outside the breast boundary, the nipple should exhibit higher gray levels than the background pixels outside the boundary. Breast boundary tracking Our breast boundary tracking method was evaluated quantitatively in a previous study. Observer variability for identifying invisible nipples For the nipples that could not be positively identified, i. Defining a small search region along the breast boundary would reduce the chance that jagged breast borders from noise and artifacts would result in false positive nipple identification. In such cases,searching for the nipple shape along the boundary could find a reliable nipple location.
As shown in Fig.
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Dense breasts generally exhibit more textural structures than fatty breasts on the mammograms. Correlation of information from multiple-view mammograms e. For the situation when the nipple was projected inside the breast boundary, the detection was complicated by noise. Within the limited nipple search region, the first step was to detect if there was a sudden and distinct change in the boundary direction, which indicated a convex nipple shape outside of the boundary. The visibility of the nipple is not limited by the resolution of the image at this pixel size. Detecting the gray level changes along the breast boundary could potentially find the true nipple location.