A 3D visualization system for computer-aided mammogram analysis

Abstract

Abstract. The most frequent symptoms of ductal carcinoma recognized by mammography are clusters of microcalcifications. Their detection from mammograms is difficult, especially for glandular breasts. We present a new system for computer-aided diagnosis of breast carcinoma, from digital mammograms. The images are processed 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. We present to radiologist for visual analysis, such a contrast-enhanced mammogram, with the suggested positions of microcalcification clusters. Finally, the radiologist, makes a more sophisticated diagnosis based on 3D visualization environment. We have evaluated the usefulness of this system with the help of four experienced radiologists, who found that this approach produces a significant improvement in the diagnosis.

Download PDF:
_{Sorry, we are unable to provide the full text but you may find it at the following location(s):}

http://citeseerx.ist.psu.edu/v... (external link)

http://www.dtc.umn.edu/publica... (external link)