3-D Correlation-Based Speckle Tracking

Abstract

Widely-used 1-D/2-D speckle tracking techniques in elasticity imaging often experience significant speckle decorrelation in applications involving large elevational motion (i.e., out of plane motion). The problem is more pronounced for cardiac strain rate imaging (SRI) since it is very difficult to confine cardiac motion to a single image plane. Here, we present a 3-D correlation-based speckle tracking algorithm. Conceptually, 3-D speckle tracking is just an extension of 2-D phase-sensitive correlation-based speckle tracking. However, due to its high computational cost, optimization schemes, such as dynamic programming, decimation and two-path processing, are introduced to reduce the computational burden. To evaluate the proposed approach, a 3-D bar phantom under uniaxial compression was simulated for benchmark tests. A more sophisticated 3-D simulation of the left ventricle of the heart was also made to test the applicability of 3-D speckle tracking in cardiac SRI. Results from both simulations clearly demonstrated the feasibility of 3-D correlation-based speckle tracking. With the ability to follow 3-D speckle in 3-D space, 3-D speckle tracking outperforms lower-dimensional speckle tracking by minimizing decorrelation caused by pure elevational translation. In other words, 3-D tracking can push toward solely deformation-limited, decorrelation-optimized speckle tracking. Hardware implementation of the proposed 3-D speckle tracking algorithm using field programmable gate arrays (FPGA) is also discussed.

Three-Dimensional Speckle-Tracking Imaging for Left Ventricular Rotation Measurement

“…10,11 Tracking is dependent on image quality and is vulnerable to dropouts of ultrasound data and reverberation. Moreover, some clinical studies have reported that 2D STI has limited feasibility or wide variability in the values for LVrot.…”

“…16,23 Three-Dimensional SPI for Rotation Measurement With the advent of real-time 3D ultrasound in echocardiography, 10,11 3D STI using real-time 3D data sets will certainly become increasingly attractive. 24 Chen et al 10 have shown the feasibility of 3D STI on 3D ultrasonic data sets and that 3D STI was better than 2D SPI for cardiac strain imaging. Abe et al 13 have used 3D STI to accurately detect regional radial strain and ejection function in a 3D LV model.…”

“…9 However, because of the 3-dimensional (3D) nature of cardiac deformation, 2D STI based on 2D imaging may not be robust enough for LVrot measurement because of speckle decorrelation or the loss of some speckles due to elevational motion (ie, through-plane motion). 9,10 The problem is more pronounced for cardiac twist because it requires multiple short-axis (SAX) views. 10,11 Three-dimensional STI programs have appeared recently, which attempt to overcome the limitations of 2D STI for LVrot measurement.…”

“…10,11 Three-dimensional STI programs have appeared recently, which attempt to overcome the limitations of 2D STI for LVrot measurement. [10][11][12] We sought to examine the accuracy of a new 3D STI program for LVrot measurement.…”

3D Cardiac Segmentation Using Temporal Correlation of Radio Frequency Ultrasound Data

“…Temporal correlations might thus be used as a feature for distinguishing between blood and the heart muscle. For 3D strain imaging purposes, the cross-correlation function (CCF) of 2D windows of rf-data was calculated [8], [9] using two subsequent full volumes. The peak of the crosscorrelation function reveals the displacement of a 2D segment of rf-data in the next time frame in 2D space.…”