Combining Clinical, Sonographic, and Elastographic Features to Improve the Detection of Prostate Cancer.

摘要

The goal of this project is to combine features derived from ultrasound (US) images, US radio frequency (RF) data, tissue elasticity imaging, and clinical data such as PSA into a computerized system for displaying prostate images that indicate probable location(s) of cancer RF data are acquired from in-vitro prostatectomy specimens in cross sectional planes 2mm apart. These data are used to calculate RF features such as backscatter coefficient and are also used to generate images and elastograms from which image texture features and tissue strain are computed. These features are correlated with histology from the same location in the prostate to determine which feature combinations accurately predict the presence of cancer.