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Computerized identification of suspicious regions for masses in digitized mammograms
1Department of Radiology, University of Pittsburgh, Pennsylvania 15261-0001, USA.
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.