Detection of clustered microcalcifications in small field digital mammography

Authors:
Tomasz Arod;Marcin Kurdziel;Tadeusz J. Popiela;Erik O. D. Sevre;David A. Yuen
Affiliations:
Institute of Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland;Institute of Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland;Collegium Medicum, Jagiellonian University, ul. Kopernika 19, 31-501 Kraków, Poland;Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA;Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA
Venue:
Computer Methods and Programs in Biomedicine
Year:
2006

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Abstract

The most frequent symptoms of ductal carcinoma recognised by mammography are clusters of microcalcifications. Their detection from mammograms is difficult, especially for glandular breasts. We present a new computer-aided detection system for small field digital mammography in planning of breast biopsy. The system processes the mammograms in several steps. First, we filter the original picture with a filter that is sensitive to microcalcification contrast shape. Then, we enhance the mammogram contrast by using wavelet-based sharpening algorithm. Afterwards, we present to radiologist, for visual analysis, such a contrast-enhanced mammogram with suggested positions of microcalcification clusters. We have evaluated the usefulness of the system with the help of four experienced radiologists, who found that it significantly improves the detection of microcalcifications in small field digital mammography.