Improved Background Noise Suppression and Microbubbles Localization for Ultrasound Localization Microscopy Using Acoustic Sub-Aperture Processing

Ultrasound localization microscopy (ULM) has been rapidly developed to visualize microvasculature on the micrometer scale by localizing and tracking the spatially isolated microbubbles (MBs). One of the key technologies used by ULM is ultra-high-frame-rate plane wave imaging. However, due to the unfocused transmission, the penetration is limited and the signal-to-noise ratio (SNR) is low, which makes it challenging to differentiate background noise from MBs. Acoustic sub-aperture processing (ASAP) has been proposed in power Doppler imaging to suppress background noise. In this study, we introduce ASAP beamforming method to the ULM processing chain (ASAP-ULM) by replacing conventional delay-and-sum (DAS) beamformer for better noise suppression and less false localization induced by noise. The ULM intensity results of a diabetic rat kidney show that the proposed method can effectively suppress background noise and obtain more continuous and filling microvessels than those obtained by conventional DAS-ULM.

[1]  K. Hansen,et al.  Super-Resolution Ultrasound Imaging Provides Quantification of the Renal Cortical and Medullary Vasculature in Obese Zucker Rats: A Pilot Study , 2022, Diagnostics.

[2]  O. Couture,et al.  Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy , 2022, Nature Biomedical Engineering.

[3]  Jianwen Luo,et al.  In Vivo assessment of hypertensive nephrosclerosis using ultrasound localization microscopy. , 2021, Medical physics.

[4]  Jianwen Luo,et al.  In Vivo Assessment of Diabetic Kidney Disease using Ultrasound Localization Microscopy , 2021, 2021 IEEE International Ultrasonics Symposium (IUS).

[5]  H. Liao,et al.  Improved Background Noise Suppression in Ultrasound Localization Microscopy using Spatial Coherence Beamforming , 2021, 2021 IEEE International Ultrasonics Symposium (IUS).

[6]  Armando Manduca,et al.  Kalman Filter-Based Microbubble Tracking for Robust Super-Resolution Ultrasound Microvessel Imaging , 2020, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[7]  Chee Hau Leow,et al.  ASAP: Super-Contrast Vasculature Imaging Using Coherence Analysis and High Frame-Rate Contrast Enhanced Ultrasound , 2018, IEEE Transactions on Medical Imaging.

[8]  Armando Manduca,et al.  Improved Super-Resolution Ultrasound Microvessel Imaging With Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking , 2018, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[9]  Mickael Tanter,et al.  Subwavelength motion-correction for ultrafast Ultrasound Localization Microscopy , 2017, 2017 IEEE International Ultrasonics Symposium (IUS).

[10]  M. Tanter,et al.  Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging , 2015, Nature.

[11]  M. Fink,et al.  Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography , 2009, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[12]  Harold W. Kuhn,et al.  The Hungarian method for the assignment problem , 1955, 50 Years of Integer Programming.