Fundamental performance metrics and optimal image processing strategies for ultrasound systems

Fundamental limits on imaging system performance are developed using Bayesian signal detection theory. The analysis expands upon the well-known theory of Smith and Wagner. Envelope-detected signals are shown to be sub-optimal for detection tasks. Two image processing strategies are presented that may improve upon current B-mode processing: deconvolution and wavefront curvature matched filtering. The later technique takes advantage of remarkable spatial-frequency bandwidths available in curved wavefronts to obtain high quality images. Both techniques attempt to approach the fundamental limits of performance by mimicking the strategy of the ideal observer.