Efficient Two-Pass 3-D Speckle Tracking for Ultrasound Imaging

Abstract

Speckle tracking based on block matching is the most common method for multi-dimensional motion estimation in ultrasound elasticity imaging. Extension of two-dimensional (2-D) methods to three dimensions (3-D) has been problematic because of the large computational load of 3-D tracking, as well as performance issues related to the low frame (volume) rates of 3-D images. To address both of these problems, we have developed an efficient two-pass tracking method suited to cardiac elasticity imaging. PatchMatch, originally developed for image editing, has been adapted for ultrasound to provide first-pass displacement estimates. Second-pass estimation uses conventional block matching within a much smaller search region. 3-D displacements are then obtained using correlation filtering previously shown to be effective against speckle decorrelation. Both simulated and in vivo canine cardiac results demonstrate that the proposed two-pass method reduces computational cost compared to conventional 3-D exhaustive search by a factor of 10. Moreover, it outperforms one-pass tracking by a factor of about 3 in terms of root-mean-square error relative to available ground-truth displacements.

Real-time interleaved spectroscopic photoacoustic and ultrasound (PAUS) scanning with simultaneous fluence compensation and motion correction

“…Interleaved data acquisition provides simultaneous anatomic (US) and PA images at a 50 Hz frame rate. This is sufficient for US speckle tracking 56 of individual pixels to map tissue motion between sequential images at different wavelengths (Fig. 2c ).…”

“…A frame composed of 1 B-mode and 20 PA sub-images is produced within 20 ms (50 Hz effective imaging frame rate). c The interframe tissue motion map is obtained using US speckle-tracking 56 , then applied to all pixels of co-registered PA images. Blue and yellow circles show local motion between adjacent frames, whereas a green circle fixed in location clearly shows the efficacy of motion correction.…”

Real-time spectroscopic photoacoustic/ultrasound (PAUS) scanning with simultaneous fluence compensation and motion correction for quantitative molecular imaging

“…c, Illustration on how high frame-rate B-mode US co-registered with PA images helps correct motion artifacts in PA images recorded at different wavelengths. The inter-frame tissue motion map is obtained using US speckle-tracking [50], then applied to all pixels of the co-registered PA images. Although US image coherence is quickly lost over a complete set of B-mode images in a sequence, tissue motion between adjacent B-mode frames can nearly always be tracked, accumulated over a sequence interval, and then applied to all PA images recorded at different wavelengths.…”

“…Interleaved data acquisition provides simultaneous anatomic (US) and molecular (PA) images at a 50 Hz frame rate. This rate is sufficient for US speckle tracking [50] of individual pixels to map tissue motion between sequential images at different wavelengths ( Fig. 2c).…”

“…Motion compensation, the first step in PA image reconstruction, is performed over each spectroscopic PAUS frame by estimating the relative displacement among 10 US B-mode images corresponding to PA images with 10 different wavelengths. The displacement between two successive B-mode images is computed and then accumulated relative to the first image in the composite spectroscopic frame using a recently developed speckle tracking approach[50]. It is relatively efficient because it leverages a randomized search called PatchMatch[69] (Supplementary Note 9).…”