Mammographic parenchymal pattern has been associated with risk of developing breast cancer. Currently, these patterns are classified subjectively by radiologists according to "Wolfe grade", as N, P1, P2, or DY. Such broad classifications have limited applicability for the assessment of subtle changes which may occur, for example, in long term studies of women at high risk for breast cancer. For such work, a consistent, quantitative, observer-independent method of characterization is required. We have been developing such a method based on the use of "fractals". We have applied techniques of calculating fractal dimension to digitized mammograms. To evaluate our technique, we are measuring the degree of correlation between the fractal classification of images and their mammographic patterns as assessed by radiologists. Preliminary results have shown significant correlation between the fractal-based and radiologist-based assessments.