Detection of clustered microcalcifications in small field digital mammography.
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.
Arodź
Tomasz
T
Institute of Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland. arodz@agh.edu.pl
Kurdziel
Marcin
M
Popiela
Tadeusz J
TJ
Sevre
Erik O D
EO
Yuen
David A
DA
D000465:Algorithms; D001941:Breast Diseases / Q000175:diagnosis; D001943:Breast Neoplasms / Q000175:diagnosis*; D002114:Calcinosis / Q000473:pathology*; D016000:Cluster Analysis; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008327:Mammography / Q000379:methods*; D012372:ROC Curve; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results