Out-of-plane motion estimation based on a Rician-Inverse Gaussian model of RF ultrasound signals: speckle tracking without fully developed speckle

Abstract

Fully developed speckle has been used previously to estimate the out-of-plane motion of ultrasound images. However, in real tissue the rarity of such patterns and the presence of coherency diminish both the precision and the accuracy of the out-of-plane motion estimation. In this paper, for the first time, we propose a simple mathematical derivation for out-ofplane motion estimation in which the coherent and non-coherent parts of the RF echo signal are separated. This method is based on the Rician-Inverse Gaussian stochastic model of the speckle formation process, which can be considered as a generalized form of the K-distribution with richer parameterization. The flexibility of the proposed method allows considering any patch of the RF echo signal for the purpose of displacement estimation. The experimental results on real tissue demonstrate the potential of the proposed method for accurate out-of-plane estimation. The underestimation of motion in ex vivo bovine tissue at 1 mm displacement is reduced to 15.5% compared to 37% for a base-line method.

Sensorless Out-of-Plane Displacement Estimation for Freehand 3D Ultrasound Applications

“…As it was mentioned briefly in section 2.1, the deviation of a coherent field phase front from its original form after encountering a random medium, causes a granular noisy pattern in ultrasound images so-called as speckle. In fact, speckle is a meaningful signal instead of only being a random noise; therefore, it can be applied in order to manifest information of the imaging system or the random medium [48].…”

“…This technique leads to the creation of the adapted elevational decorrelation curves which allow for the effect of coherent scattering to be considered. Another example is in [48] where a framework is created to separate coherent and non-coherent effects in every patch of the images based on a Rician Inverse Gaussian (RiIG) statistical model.…”

Distance Estimation for 3D Freehand Ultrasound-Scans with Visualization System

“…An objective of this thesis is to determine the displacement between two image planes based on the change of the backscattered signal at two different positions. Afsham et al [40], [41] describe how reflected signals obtained from transducers have information from both the medium and the ultrasound beam.…”

“…According to Afsham et al [40], [41], one characteristic of the ultrasound beam is that it remains constant during use. Hence, a change in the medium from the change in speckle interprets the image plane motion for estimating the elevation distance.…”

“…Consequently, researchers have been investigating ways to remove tracking devices through speckle tracking. Recently, Afsham et al [40], [41] applied speckles in the images to estimate elevation distances between frames in the 3D coordinate system.…”