Mammographic density increases the risk for developing breast cancer and delays clinical detection of the tumor. High-throughput density measures are available for original (raw) digital mammograms in the clinical setting and for analog film mammograms in research settings. These measures are based on different techniques and are not comparable. Secondly, digital raw mammograms in clinical use today are stored as processed images at reduced quality to lower storage costs, and currently there is no established automated method for measuring mammographic density on these images. We are developing a novel high-throughput method which measures mammographic density on stored processed and analog images with a risk predicting quality comparable to clinically accepted measures available on raw mammograms.