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

F. Tortorella
;
2012

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4721799
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