Computerized identification of suspicious regions for masses in digitized mammograms.

RATIONALE AND OBJECTIVES

A simple and effective computerized detection scheme was developed to identify suspicious mass regions in digitized mammograms.

METHODS

This method identifies a maximum of five suspicious mass regions per image and was tested with a database of 510 images, including 162 verified masses. It includes a series of five rule-based processes that select one region with each of the following characteristics: 1) a global minimum of optical density in a smoothed image; 2) a local minimum of optical density in the original image; 3) a local minimum of optical density in a filtered image; 4) a small "mass" of low contrast; and 5) a small "mass" of high contrast.

RESULTS

This multi-stage process achieved a sensitivity of 95% while limiting false-positive detection rates to below an average of two per image.

CONCLUSION

Because this method limits the initial number of suspicious mass regions while retaining high sensitivity, it may be applicable to clinically usable computer-aided diagnosis schemes.