Early correct diagnosis of breast cancer can mean the difference between life and death for the significant proportion of western women affected by the disease. Small clumps of calcium salts - microcalcifications - are often the earliest signs of breast cancer, and appear in 25 percent of mammograms. Oxford University researchers have developed a new method to identify more reliably these clusters.

Calcifications appear as bright spots or clusters of spots; small clustered whorled calcifications are those most likely to indicate malignancy. The existence of microcalcifications in a mammogram is a clear warning of abnormality. Any program to assist a radiologist detect microcalcifications must miss few, if any, clinically important clusters, but equally must not signal too many false positives.

These calcifications are usually large, few in number, widely dispersed, and round. The term microcalcifications is often used for the smaller calcifications that are associated with malignancy; microcalcifications are usually more numerous, clustered, and variously shaped (rods, branches, teardrops). Between benign and suspicious calcifications is a gray zone of "hard to tell"? calcifications which are often labeled indeterminate. Since physicians' recommendations regarding indeterminate calcifications differ, women need to inform themselves about diagnostic options.

When calcifications are thought to be associated with benign conditions, a routine mammogram is called for in one or two (or more) years, depending on a woman's age and risk factors. When suspicious micro-calcifications appear on a mammogram, but no lump is felt, either a needle-localization biopsy or a sterotactic core biopsy is recommended, so that breast tissue can be removed and examined under a microscope by a pathologist. These two kinds of biopsies are the only ways to find out whether indeterminate microcalcifications are associated with cancer.

With the increasingly vast number of mammograms to be analyzed from screening programs, automated computer-aided detection methods are a necessity. Although several methods have been proposed for detecting microcalcification clusters, they have all been limited by faults such as the return of too many false positives.

Oxford researchers, however, have recently developed a foveal segmentation method, based on differential local contrast in the image, that will significantly reduce the risk of both false negatives and false positives in identifying calcifications in mammograms.

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