recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. it is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. in this paper, f...

The purpose of this study was to determine whether the interpretation of microcalcifications assessed on images zoomed (x 2.0) from digital mammograms is at least equivalent to that from digital magnification mammography (x 1.8) with respect to diagnostic accuracy and image quality. Three radiologists with different levels of experience in mammography reviewed each full-field digital mammograph...

In this paper we present a new approach for computer aided detection of microcalcifications (MC) clusters in mammograms. The proposed method is done in two stages; the first stage is a preprocessing with histogram, in the second stage the ability of these filtered images in detecting microcalcification is done using the Curvelet Transform. The proposed method is applied to a database of 10 dens...

Mammography is the most efficient method for breast cancer early detection. Clusters of microcalcifications are the sign of breast cancer and their early detection is the key to improve breast cancer prognosis. Microcalcifications appear in mammogram as tiny granular points, which are difficult to observe by radiologists due to their small size. An efficient method for automatic and accurate de...

Microcalcifications are small crystals of calcium apatites which form in human tissue through a number of mechanisms. The size, morphology, and distribution of microcalcifications are important indicators in the mammographic screening for and diagnosis of various carcinomas in the breast. Although x-ray mammography is currently the only accepted method for detecting microcalcifications, its eff...