Breast Cancer is a disease that is prevalent in many countries. Computer-Aided detection (CAD) systems have been developed to assist radiologists in detecting breast cancer. This paper discusses an algorithm for architectural distortion (AD) detection with a better sensitivity than the current CAD systems. 19 images containing ADs were preprocessed with a median filter and Gabor filters to extract texture information. AD probability maps were generated using a maximum amplitude map and histogram analysis on the orientation map of the Gabor filter response. AD maps were analyzed to select ROIs as potential AD sites. AD map analysis yielded a sensitivity of 79% (15 out of 19 cases of AD were detected) with a false positive per image (FPI) of 18. Future work involves the development of a second stage in the algorithm to reduce the FPI value and application of the algorithm to a different set of database images. © IFIP International Federation for Information Processing 2013.
CITATION STYLE
Ejofodomi, O., Olawuyi, M., Onyishi, D. U., & Ofualagba, G. (2013). Detecting architectural distortion in mammograms using a Gabor filtered probability map algorithm. In IFIP Advances in Information and Communication Technology (Vol. 412, pp. 328–335). Springer New York LLC. https://doi.org/10.1007/978-3-642-41142-7_34
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