AGH University of Science & Technology, Karkow

Techniques for automatic detection of anomalies in mammograms studied

Published in Disease Risk Factor Week, October 16th, 2005

Pattern recognition techniques for automatic detection of suspicious-looking anomalies in mammograms studied.

"We have employed two pattern recognition methods used commonly for face recognition in order to analyze digital mammograms. The methods are based on novel classification schemes, the AdaBoost and the support vector machines (SVM)," investigators in Poland report.

"A number of tests have been carried out to evaluate the accuracy of these two algorithms under different circumstances for the AdaBoost classifier method are promising, especially for classifying mass-type Lesions. In the best case the algorithm achieved accuracy of 76% for all...

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Source: Disease Risk Factor Week (2005-10-16)

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