Improved Background Noise Suppression in Ultrasound Localization Microscopy using Spatial Coherence Beamforming

Recently, the resolution of ultrasound imaging has been dramatically increased using ultrasound localization microscopy (ULM), by localizing the spatially isolated microbubbles (MBs). However, owing to the poor penetration and low signal-to-noise ratio (SNR) of plane wave (PW) imaging, it could be challenging to accurately differentiate the isolated MB signal from the background noise. In this study, we propose to utilize short-lag spatial coherence (SLSC) beamformer to suppress the background noise (including residual tissue clutters and electronic noise) based on the high spatial coherence of MB echo signals. Using in vivo data, the proposed method has effectively suppressed noise and preserved the MB signals. Therefore, the number of falsely-detected MBs was reduced to provide a more robust MB localization for ULM.