Two-Stage Motion Correction for Super-Resolution Ultrasound Imaging in Human Lower Limb

Abstract

The structure of microvasculature cannot be resolved using conventional ultrasound (US) imaging due to the fundamental diffraction limit at clinical US frequencies. It is possible to overcome this resolution limitation by localizing individual microbubbles through multiple frames and forming a superresolved image, which usually requires seconds to minutes of acquisition. Over this time interval, motion is inevitable and tissue movement is typically a combination of large- and small-scale tissue translation and deformation. Therefore, super-resolution (SR) imaging is prone to motion artifacts as other imaging modalities based on multiple acquisitions are. This paper investigates the feasibility of a two-stage motion estimation method, which is a combination of affine and nonrigid estimation, for SR US imaging. First, the motion correction accuracy of the proposed method is evaluated using simulations with increasing complexity of motion. A mean absolute error of 12.2 was achieved in simulations for the worst-case scenario. The motion correction algorithm was then applied to a clinical data set to demonstrate its potential to enable in vivo SR US imaging in the presence of patient motion. The size of the identified microvessels from the clinical SR images was measured to assess the feasibility of the two-stage motion correction method, which reduced the width of the motion-blurred microvessels to approximately 1.5-fold.

3-D Motion Correction for Volumetric Super-Resolution Ultrasound Imaging

“…The motion estimation used here is based on an image registration approach which was previously proposed for in vivo 2-D SR-US imaging [5]. MATLAB (The MathWorks, Natick, MA) codes are currently available to download [19].…”

“…Firstly, the SNR of the imaging system must be sufficiently high and the microbubble localization method must be able to identify individual microbubbles. The second limitation is any error introduced by motion during image acquisition [4], [5]. SR-US imaging and other imaging modalities based on multiple acquisitions are prone to motion artefacts that can usually be compensated by applying motion correction algorithms.…”

“…The aim of this study is to reduce the error introduced by motion in SR-US imaging by using a 3-D extension of the two-stage motion correction method [4], [5]. To acquire realistic motion, a 2-D handheld probe was used to image a wire phantom with a volumetric imaging rate of 333 Hz.…”

3-D Super-Resolution Ultrasound Imaging With a 2-D Sparse Array

“…In the absence of tissue and probe motion, localization precision determines the maximum achievable resolution, which can be on the order of several micrometers at clinical ultrasound frequencies [1], [2]. If motion is present and subsequently corrected post-acquisition, then the motion correction accuracy can limit the achievable spatial resolution [3], [4]. Researchers demonstrated the use of 2-D super-resolution ultrasound (SR-US) imaging in many different controlled experiments and pre-clinical studies using microbubbles [5]- [12] and nanodroplets [13]- [16].…”

3-D Super-Resolution Ultrasound Imaging Using a 2-D Sparse Array with High Volumetric Imaging Rate

“…In the absence of sample motion, it is this localization precision that determines the maximum achievable resolution in super-resolution images. If motion is present and subsequently corrected post-acquisition, then the motion correction accuracy can also limit the achievable spatial resolution [3], [4]. Researchers demonstrated the use of 2-D SR-US imaging in many studies using microbubbles [5]- [13] and nanodroplets [14]- [16].…”