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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 56-65 |
| Number of pages | 10 |
| Journal | Computer Methods and Programs in Biomedicine |
| Volume | 81 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2006 |
Bibliographical note
Funding Information:We thank Ben Holtzman, Lilli Yang and Katya Shukh for their artistic rendering. This research has been supported by a grant from the University of Minnesota Digital Technology Center, grant on wavelet analysis from CMG of National Science Foundation, the Polish State Committee for Scientific Research (KBN) research grant no. 3 T11C 059 26 and the Polish Ministry of Science and Information Society Technologies grant no. 3 T11F 019 29.
Keywords
- 2D filtering
- Mammogram analysis
- Microcalcification detection
- Wavelets