University of Washington - Department of Statistics
Medical professionals and researchers used a variety of imaging techniques in their clinical practice and scientific investigations. In this talk I will focus on Mammography which is used for breast examinations and routine breast cancer screening. While the mammographic images proved to be a useful non-invasive tool for clinical monitoring, the images often luck detail and clarity. For example, in addition to having limited spatial resolution, skin-air boundary of the imaged breast is often obscured. This boundary is, however, an important initial step in the breast density estimation. Breast density, defined as a proportion of the breast tissue that appears bright on the image, was shown by various research groups to be strongly associated with the risk of breast cancer. In this work we introduce the algorithm to address the boundary detection issue, the first step in density estimation problem. The performance of the method will be demonstrated on the simulated data. We then show the boundary recovery results for the mammogram images and discuss its advantages and possible improvements.