It is important to realize that mammographic image analysis is an extremely challenging task ... Digital Database of Scr
Reducing false-positive detections by combining two stage-1 computer-aided mass detection algorithms a
Noah D. Bedarda, Mehul P. Sampata, Patrick A. Stokesa, and Mia K. Markey a * Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA ABSTRACT
In this paper we present a strategy for reducing the number of false-positives in computer-aided mass detection. Our approach is to only mark "consensus" detections from among the suspicious sites identified by different “stage-1” detection algorithms. By “stage-1” we mean that each of the Computer-aided Detection (CADe) algorithms is designed to operate with high sensitivity, allowing for a large number of false positives. In this study, two mass detection methods were used: (1) Heath and Bowyer’s algorithm based on the average fraction under the minimum filter (AFUM) and (2) a low-threshold bi-lateral subtraction algorithm. The two methods were applied separately to a set of images from the Digital ,(1
