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.

Pruning the nodule candidate set in postero anterior chest radiographs / P. Campadelli, E. Casiraghi - In: Biological and artificial intelligence environments : 15th Italian workshop on neural Nets, WIRN VIETRI 2004 : Vietri sul Mare, Italy, 2004 / [a cura di] B. Apolloni, M. Marinaro, R. Tagliaferri. - Dordrecht : Springer, 2005. - ISBN 9789048168637. - pp. 37-43

Pruning the nodule candidate set in postero anterior chest radiographs

P. Campadelli;E. Casiraghi
2005

Abstract

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.
CAD systems ; Neural networks ; Support vector machines
Settore INF/01 - Informatica
2005
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/178884
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