By Noor Nakhaei
Computer Science graduate student — Dr. Will Hsu Lab
Microcalcifications are a common finding on screening mammography: annually, approximately 580,000 exams in the United States have microcalcifications that prompt further diagnostic workup. Radiologists use rudimentary imaging features to stratify biopsy recommendations for microcalcifications. These imaging features are limited to those that are visible and describable by the radiologist using a limited set of qualitative descriptions. Novel quantitative assessment of microcalcifications has the potential to provide more accurate predictive evidence of early aggressive disease. In this project, we seek to improve the characterization of suspicious microcalcifications by analyzing their shapes, distributions, and texture patterns using quantitative analysis. We are investigating ways to spatially localize biopsy specimens to regions within 2D mammography images. We do this by jointly analyzing the microcalcifications and the surrounding tissue in diagnostic mammograms and the corresponding specimen radiograph images of the biopsy cores taken from that region. We then correlate histopathological features extracted from digital whole slide images to features extracted from matched regions on 2D mammograms.