Influence of ultrasound speckle tracking strategies for motion and strain estimation

Abstract

Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system.

Introduction to speckle tracking in cardiac ultrasound imaging

“…A simple though standard block-matching method is to compare the intensities of the pixels using the sum of absolute/squared differences measure [13]. Among a number of similarity criteria, the normalized cross-correlation was historically the first [7], and is still one of the most applied methods, in medical ultrasound imaging [14][15][16][17]. In the following, although different similarity criteria can be used, we thus focus on the normalized cross-correlation without loss of generality.…”

Test-Time Training for Deformable Multi-Scale Image Registration

“…3 and 4. Inspired by the improvement of multi-scale registration in conventional registration [41], we further employ a multiscale scheme to estimate accurate deformation where we conduct test-time training with a U-Net [42] to model the residual registration field in each scale.…”

Ultrasonic biomechanics method for vortex and wall motion of left ventricle: a phantom and in vivo study

“…The recent research works have proposed novel frame-by-frame techniques, to track speckles in two-dimensional echocardiography gray-scale images, for overcoming the angel dependence of tissue Doppler imaging [ 20 , 21 ]. Speckle tracking is a method that is suitable for measuring the myocardial motion with speckle tracking patterns in ultrasound B-mode acquisitions [ 22 ].…”