" Detecting Clusters of Microcalcifications with a Cascade-Based Approach. "

Authors

A. Bria, C. Marrocco, M. Molinara, F. Tortorella


Abstract

In this paper we present a cascade-based framework to detect clusters of microcalcifications on mammograms. The algorithm is based on a sliding window technique where a detector is structured as a “cascade” of simple boosting classifiers with increasing complexity. Such a method couples the effectiveness of the cascade approach with the RankBoost algorithm that is aimed at maximizing the area under the ROC curve and represents a good choice when dealing with unbalanced data sets.


Doi :
10.1007/978-3-642-31271-7_15                
Published in :

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