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An automated system that can provide feedback about aesthetic value or quality of headshot photos based on learned rules could be a very useful support in photo searching, sorting and editing. This is a challenging problem as it requires semantic understanding of photos, which is beyond the state-of-the-art in computer vision. In this paper, we present a method built on most important rules or guidelines...
The first step in computer aided detection (CAD) in mammography relies on accurate image segmentation. Testing of CAD algorithms should include comparison with other proposed methods in order to show how a new method compares with ones presented before. Two most popular mammographic databases, which are publicly available, consist of scanned films. This presents a segmentation challenge in order to...
Mammographic image registration is an important step in the analysis of differences between the left and right breast in order to detect bilateral asymmetry, which is an early sign of breast cancer. We have used rigid registration to align left and right mammographic images as a first step for comparing corresponding regions in the left and right breast. Registration performance was tested on a dataset...
Mammography is probably the best method for early detection of abnormalities in the breast tissue. Higher breast tissue densities significantly reduce the overall detection sensitivity and can lead to false negative results. In automatic detection algorithms, knowledge about breast density can also be useful for setting an appropriate threshold. It is impossible to produce satisfactory classification...
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