Multi-covariate Imaging of Sub-resolution Targets

Conventional B-mode ultrasound imaging assumes that targets consist of collections of point scatterers. Diffraction, however, presents a fundamental limit on a scanner's ability to resolve individual scatterers in most clinical imaging environments. Well-known optics and ultrasound literature has characterized these diffuse scattering targets as spatially incoherent and statistically stationary. In this paper, we apply a piecewise-stationary statistical model to diffuse scattering targets, in which the covariance of backscattered echoes can be described as the linear superposition of constituent components corresponding to echoes from distinct spatial regions in the field. Using this framework, we present Multi-covariate Imaging of Sub-resolution Targets (MIST), a novel estimation-based method to image the statistical properties of diffuse scattering targets, based on a decomposition of aperture domain spatial covariance. The mathematical foundations of the estimator are analytically derived, and MIST is evaluated in phantom, simulation, and in vivo studies, demonstrating consistent improvements in contrast-to-noise ratio and speckle statistics across imaging targets, without an apparent loss in resolution.