Abstract
This paper proposes a method for detection of abnormalities in mammograms that could be integrated into a computer-aided diagnosis system. The method is based on segmentation using a clustering method, elimination of small regions, blobs and contour detection and a density analysis. The method was tested on images from screening mammography databases and the results are compared with the selections realized by specialists. The tests show that the method offers good results on images that present well defined abnormalities and by adjusting some parameters it can even detect distortions difficult to be noticed by physicians.
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Chiorean, L.D., Vaida, M.F., Striletchi, C. (2017). Abnormalities Identification in Mammograms. In: Vlad, S., Roman, N. (eds) International Conference on Advancements of Medicine and Health Care through Technology; 12th - 15th October 2016, Cluj-Napoca, Romania. IFMBE Proceedings, vol 59. Springer, Cham. https://doi.org/10.1007/978-3-319-52875-5_44
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DOI: https://doi.org/10.1007/978-3-319-52875-5_44
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