Detection of clustered microcalcifications in small field digital mammography

Comput Methods Programs Biomed. 2006 Jan;81(1):56-65. doi: 10.1016/j.cmpb.2005.10.002. Epub 2005 Nov 28.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Breast Diseases / diagnosis
  • Breast Neoplasms / diagnosis*
  • Calcinosis / pathology*
  • Cluster Analysis
  • Diagnosis, Computer-Assisted
  • Humans
  • Image Processing, Computer-Assisted
  • Mammography / methods*
  • ROC Curve
  • Radiographic Image Enhancement
  • Radiographic Image Interpretation, Computer-Assisted
  • Reproducibility of Results