Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

Abstract

Abstract-Acoustic super-resolution imaging has allowed visualization of microvascular structure and flow beyond the diffraction limit using standard clinical ultrasound systems through the localization of many spatially isolated microbubble signals. The determination of each microbubble position is typically performed by calculating the centroid, finding a local maximum, or finding the peak of a 2-D Gaussian function fit to the signal. However, the backscattered signal from a microbubble depends not only on diffraction characteristics of the waveform, but also on the microbubble behavior in the acoustic field. Here, we propose a new axial localization method by identifying the onset of the backscattered signal. We compare the accuracy of localization methods using in vitro experiments performed at 7 cm depth and 2.3 MHz center frequency. We corroborate these findings with simulated results based on the Marmottant model. We show experimentally and in simulations that detecting the onset of the returning signal provides considerably increased accuracy for super-resolution. Resulting experimental crosssectional profiles in super-resolution images demonstrate at least 5.8 times improvement in contrast ratio and more than 1.8 reduction in spatial spread (provided by 90% of the localizations) for the onset method over centroiding, peak detection and 2D Gaussian fitting methods. Simulations estimate that these latter methods could create errors in relative bubble positions as high as 900 µm at these experimental settings, while the onset method reduced the interquartile range of these errors by a factor of over 2.2. Detecting the signal onset is therefore expected to considerably improve the accuracy of super-resolution.

Quantitative sub-resolution blood velocity estimation using ultrasound localization microscopy ex-vivo and in-vivo

“…The step after the SVD filtering consists of localizing the MB positions. Several methods have been used for this purpose, such as onset detection, centroid fitting, Gaussian fitting, and others which have been previously compared (Christensen-Jeffries et al 2017). In this study, the centroid method was used due to its adequate computational performance and its ease of implementation.…”

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

“…SVD was used to separate the microbubble signals from the echoes originating from the tube and the assembly holding the tube. Localization of isolated microbubbles was performed on every acquired volume to generate the 3-D super-resolved volumes [33].…”

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

“…Motion estimation was performed on the 3-D B-mode data and microbubble locations were corrected accordingly. Localization of isolated microbubbles was performed using the onset method on every acquired volume to generate the 3-D SR-US images [27].…”