Pattern recognition techniques for automatic detection of suspicious-looking anomalies in mammograms
Computer Methods and Programs in Biomedicine
A supervised method for microcalcification cluster diagnosis
Integrated Computer-Aided Engineering
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At present, mammography is the only not invasive diagnostic technique allowing the diagnosis of a breast cancer at a very early stage. A visual clue of such disease particularly significant is the presence of clusters of microcalcifications. Reliable methods for an automatic recognition of malignant clusters are 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 for automating the recognition of malignant clusters, based on the adoption of a Multiple Expert System (MES). The approach has been successfully tested on a standard database of 40 mammographic images, publicly available.