Evaluation of microcalcifications segmentation techniques for dense breast digitized images

Some processing techniques cited in the literature used for microcalcifications detection in digitized mammograms are evaluated here with regard to dense breast images. Three techniques were investigated: Nappi et al.'s, Nishikawa et al.'s and Wallet et al.'s. The methods were tested with low-contrast phantom images, simulating dense breast images. The ability of each technique to detect microcalcifications in dense breast images was evaluated. The following detection rates were obtained: Nappi et al's technique, 78.3%; Wallet et al.'s, 86.6%; and Nishikawa et al.'s, 94.4%. Dense breast images affect the performance of CAD schemes, as confirmed by our results. Therefore, data from those segmentation techniques applied to dense breast images could be improved by developing a hybrid method using the best characteristics of each technique.