The presence of clusters of microcalcifications in mam- mograms is particularly significant for early detection of breast cancer. In this paper a Computer Aided Detection system designed for this task is described. The detection of microcalcifications is performed by means of a segmen- tation based on a watershed transform and a further anal- ysis based both on heuristic rules and AdaBoost classifi- cation. Finally a clustering algorithm is applied to detect those clusters of medical interest. The approach has been successfully tested on a Full Field Digital Mammographic database that has been developed through a strong cooper- ation between radiologists and computer scientists.
Detection of cluster of microcalcifications based on watershed segmentation algorithm
MARROCCO, Claudio;MOLINARA, Mario;TORTORELLA, Francesco;
2012-01-01
Abstract
The presence of clusters of microcalcifications in mam- mograms is particularly significant for early detection of breast cancer. In this paper a Computer Aided Detection system designed for this task is described. The detection of microcalcifications is performed by means of a segmen- tation based on a watershed transform and a further anal- ysis based both on heuristic rules and AdaBoost classifi- cation. Finally a clustering algorithm is applied to detect those clusters of medical interest. The approach has been successfully tested on a Full Field Digital Mammographic database that has been developed through a strong cooper- ation between radiologists and computer scientists.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
