Target detectability in acoustic elastography.

The clinically relevant task of visually detecting low contrast targets in noisy strain images estimated from ultrasonic signals is studied. Detectability is measured quantitatively using contrast-to-noise ratio (CNR) analysis. Contrast in strain images is generated by a complex interaction among the soft tissue elasticity shear modulus distribution, target shape and location in the stress field, and external boundary conditions. Although a large strain variation is preferred for enhancing the contrast, this also increases the signal-dependent noise in strain estimates in a nonlinear fashion. Therefore, understanding the tradeoffs between contrast and noise is necessary for improving the diagnostic performance of strain imaging. In this paper, targets with slab, cylindrical, and spherical geometries are studied. Strains in the target and background and the precision of their estimates are described in terms of the corresponding shear modulus values for each geometry. These results are then incorporated into the CNR expression to investigate the changes in target detectability with the variation of shear modulus in the target and the ultrasonic signal parameters (echo signal-to-noise ratio and inverse fractional bandwidth) as well as the signal processing variables (time-bandwidth product and fractional window overlap).