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Helping to improve early breast cancer Detection Rates


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% of mammograms. Oxford 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. With the increasingly vast number of mammograms to be analysed from screening programmes, 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 help to significantly reduce the risk of both false negatives and false positives being made in the identification of calcifications in mammograms.

If you are interested in finding out more about this technique or if you have a commercial interest in helping to develop the technology further then contact

Kim Bruty | alfa
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