Automated detection of breast tumors using the asymmetry approach
Computers and Biomedical Research
Establishing the correspondence between control points in pairs of mammographic images
IEEE Transactions on Image Processing
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
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A method has been developed for detection masses in mammograms by analysis of local orientation patterns. Concentration of gradient and line orientation computed at a fine scale reveals the presence of masses and spiculation, respectively. In this paper a new computational approach is presented which allows efficient computation of these features as a continuous function of spatial scale. It is shown that by using these scale signatures estimates of mass size can be readily obtained. Experimentally it was found that mass size estimates can be used to improve mass detection, while full exploitation of the information represented by the scale signatures is expected lead to further improvement. Results are presented for detection of malign masses in a database of 264 mammograms representing 71 consecutive cancers found in screening.