Surface Estimation in Ultrasound Images
Stephen M. Pizer, Valen E. Johnson · 2010
Surface definition, a process of defining three dimensional surface from volume data, is essential in three dimensional volume data rendering. The traditional method applies a three dimensional gradient operator to the volume data to estimate the strength and orientation of surface present. Applying this method to ultrasound volume data does not produce satisfactory results due to noisy nature of the images and the sensitivity of certain signals to the direction of insonation. A Bayesian approach is proPosed here for surface definition of noisy images in general. We formulate the problem as the estimation of posterior means and standard deviations of Gibbs distributions for surface believability and normal direction. The prior distribution reflects shape properties at multiple scales. The design and implementation of such an approach and its application on ultrasound images are the subject of this paper.