Preprocessing for improving CAD scheme performance for microcalcifications detection based on mammography imaging quality parameters

Database characteristics can affect significantly the performance of a mammography CAD scheme. Hence adequate performance comparison among different CAD schemes is not suitable since a single scheme could present different results depending on the set of chosen cases. Images in database should follow a set of quality criteria, since the imaging process up to digital file. CAD schemes can not be developed without a database used to test their efficacy, but each database with particular characteristics may influence on the processing scheme performance. A possible solution could be using information on the imaging equipment characteristics. This work describes a preprocessing in order to "compensate" the image degradation during the acquisition steps, assuring a better "uniformity" relative to the images quality. Thus, poor quality images would be restored, providing therefore some independence on the images source to CAD schemes and allowing to reach the better possible performance. Tests performed with mammography images sets reported a 14% increase in sensitivity for microcalcifications detection. Although this result was followed by a little increase in false positive rates, simple changes in techniques parameters can provide the same improvement but with a reduction of the false positive detections.