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10th International Conference on Image Analysis and Processing (ICIAP'99)
Automatic Classification of Clustered Microcalcifications by a Multiple Expert System
Venice, Italy
September 27-September 29
ISBN: 0-7695-0040-4
S. de Vito, Universit? degli Studi di Napoli "Federico II"
M. Vento, Universit? degli Studi di Napoli "Federico II"
F. Tortorella, Universit? degli Studi di Cassino
Mammography is a not invasive diagnostic technique largely used for early cancer detection in women's breast. One of the main indicants of such disease is the presence of microcalcifications, appearing as small bright spots in the mammographic image. An automatic detection and recognition of malignant clusters of microcalcifications, although very useful for a mass screening of the female population at risk, is very difficult to accomplish because of the small size of the microcalcifications and of the poor quality of the mammographic images. In this paper we propose a novel approach, based on the adoption of a Multiple Expert System (MES). Such a system aggregates several experts, some of which are devoted to classify the single microcalcifications while others are aimed to recognize the malignancy of the cluster considered as a whole. The final classification of the system results from the combination of the outputs of the single experts. The approach has been successfully tested on a standard database of the 40 mammographic images, publicly available.
Citation:
S. de Vito, M. Vento, F. Tortorella, "Automatic Classification of Clustered Microcalcifications by a Multiple Expert System," iciap, pp.464, 10th International Conference on Image Analysis and Processing (ICIAP'99), 1999
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