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Mammography is at present the best available technique for early detection of breast cancer. The most common breast abnormalities that may indicate breast cancer are masses and calcifications. In some cases, subtle signs that can also lead to a breast cancer diagnosis, such as architectural distortion and bilateral asymmetry, are present. Breast(More)
Digital mammography is used more and more each day in comparison with screen film mammography (SFM). Main advantage of digital mammography for image processing is the use of images with few or no artifacts that can occur on SFM images. Finding breast border contour is therefore easier and gives more precise results. On the other hand, detection of pectoral(More)
Breast skin–air interface and pectoral muscle segmentation are usually first steps in all CAD applications on scanned as well as digital mammograms. Breast skin–air interface segmentation is much more difficult task when performed on scanned mammograms than on digital mammograms. In case of pectoral muscle segmentation, segmentation difficulty of analog and(More)
This paper presents a review of recent advances in the development of methods for segmentation of the breast boundary and the pectoral muscle in mammograms. Regardless of improvement of imaging technology, accurate segmentation of the breast boundary and detection of the pectoral muscle are still challenging tasks for image processing algorithms. In this(More)
Microcalcifications are an important early sign of breast cancer development. Because of that computer aided detection systems (CADe) for detection of microcalcifications can be very useful and helpful for breast cancer control. In order to perform detection and classification of microcalcifications it is necessary to achieve accurate detection. To be able(More)
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(More)
Breast cancer is the most common cancer in women. Early detection and diagnosis of breast cancer facilitated with digital mammography can increase survival rate and chances for patient's complete recovery. Bilateral asymmetry is one the breast abnormalities that may indicate breast cancer in early stage of its development. Researchers have been(More)
– Digital mammography brought many changes in the development of Computer Aided Detection (CAD) algorithms. Many preprocessing steps on mammograms are made automatically before the detection and diagnosis process begins. One of the very important steps is mammogram registration, which helps in finding asymmetrical regions in left and right breast. Mammogram(More)
Breast tissue segmentation into dense and fat tissue is important for determining the breast density in mammograms. Knowing the breast density is important both in diagnostic and computer-aided detection applications. There are many different ways to express the density of a breast and good quality segmentation should provide the possibility to perform(More)
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