Name
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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.cmpb.2005.10.002 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
contrast shape,contrast-enhanced mammogram,experienced radiologist,ductal carcinoma,breast biopsy,new computer-aided detection system,mammogram contrast,mammogram analysis microcalcification detection wavelets 2d filtering,digital mammography,small field,microcalcification cluster,visual analysis,wavelets | Sharpening,Digital mammography,Computer vision,Ductal carcinoma,Mammography,Microcalcification,Computer science,Artificial intelligence,Radiology,Breast biopsy | Journal |
Volume | Issue | ISSN |
81 | 1 | 0169-2607 |
Citations | PageRank | References |
17 | 1.34 | 16 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tomasz Arodź | 1 | 58 | 7.65 |
| Marcin Kurdziel | 2 | 55 | 8.33 |
| Tadeusz J. Popiela | 3 | 17 | 2.36 |
| Erik O D Sevre | 4 | 29 | 2.64 |
| David A. Yuen | 5 | 82 | 14.75 |