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.
2012
9781467320498
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/21526
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
social impact