Pruning the nodule candidate set in postero anterior chest radiographs

In this paper we describe and compare two different methods to reduce the cardinality of the set of candidates nodules, characterized by an high sensitivity ratio, and extracted from PA chest radiographs by a fully automatized method. The methods are a rule based system and a feed-forward neural network trained by back-propagation. Both the systems allow to recognize almost the 75% of false positives without losing any true positives