Global Ultrasound Elastography in Spatial and Temporal Domains

In this paper, a novel computationally efficient quasi-static ultrasound elastography technique is introduced by optimizing an energy function. Unlike conventional elastography techniques, three radio frequency (RF) frames are considered to devise a nonlinear cost function consisting of data intensity similarity term, spatial regularization terms and, most importantly, temporal continuity terms. We optimize the aforesaid cost function efficiently to obtain the time-delay estimation (TDE) of all samples between the first two and last two frames of ultrasound images simultaneously, and spatially differentiate the TDE to generate axial strain map. A novelty in our spatial and temporal regularizations is that they adaptively change based on the data, which leads to substantial improvements in TDE. We handle the computational complexity resulting from incorporation of all samples from all three frames by converting our optimization problem to a sparse linear system of equations. Consideration of both spatial and temporal continuity makes the algorithm more robust to signal decorrelation than the previous algorithms. We name the proposed method GUEST: Global Ultrasound Elastography in Spatial and Temporal directions. We validated our technique with simulation, experimental phantom, and in vivo liver data and compared the results with two recently proposed TDE methods. In all the experiments, GUEST substantially outperforms other techniques in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and strain ratio (SR) of the strain images.