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In Vivo Ultrasound Localization Microscopy Imaging of the Kidney's Microvasculature With Block-Matching 3-D Denoising
- Source :
- IEEE transactions on ultrasonics, ferroelectrics, and frequency control. 69(2)
- Publication Year :
- 2021
-
Abstract
- Structural abnormalities and functional changes of renal microvascular networks play a significant pathophysiologic role in the occurrence of kidney diseases. Super-resolution ultrasound imaging has been successfully utilized to visualize the microvascular network and provide valuable diagnostic information. To prevent the burst of microbubbles, a lower mechanical index (MI) is generally used in ultrasound localization microscopy (ULM) imaging. However, high-noise levels lead to incorrect signal localizations in relatively low-MI settings and deep tissue. In this study, we implemented a block-matching threedimensional (BM3D) image-denoising method, after the application of singular value decomposition filtering, to further suppress the noise at various depths. The in vitro flow-phantom results show that the BM3D method helps the significant reduction of the error localizations, thus improving the localization accuracy. In vivo rhesus macaque experiments help conclude that the BM3D method improves the resolution more than other image-based denoising techniques, such as the nonlocal means method. The obtained clutter-filtered images with fewer incorrect localizations can enable robust ULM imaging, thus helping in establishing an effective diagnostic tool.
- Subjects :
- Microscopy
Microbubbles
Acoustics and Ultrasonics
Noise (signal processing)
Computer science
business.industry
Noise reduction
Ultrasound
Kidney
Signal
Macaca mulatta
In vivo
Microvessels
Animals
Electrical and Electronic Engineering
business
Instrumentation
Mechanical index
Biomedical engineering
Subjects
Details
- ISSN :
- 15258955
- Volume :
- 69
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- IEEE transactions on ultrasonics, ferroelectrics, and frequency control
- Accession number :
- edsair.doi.dedup.....79f8af35a0687d5db0ad6ac0ad0ae80e