Improved Super-Resolution Ultrasound Microvessel Imaging with Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking

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26 Citations (Scopus)

Abstract

Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This study aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high frame rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this study, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-section profile with full width at half maximum of 57 μm could be imaged at approximately 2 cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution ~200 μm). Cortical microvessels that are 76 μm apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.

Original languageEnglish (US)
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
DOIs
StateAccepted/In press - Nov 29 2017

Fingerprint

Ultrasonics
Imaging techniques
rabbits
background noise
filters
delineation
kidneys
blood flow
breathing
noise reduction
rejection
Full width at half maximum
Noise abatement
plane waves
spatial resolution
Velocity measurement
recording
Blood
scanning
cross sections

Keywords

  • bipartite graph
  • contrast microbubbles
  • Filtering
  • Imaging
  • microbubble tracking
  • microvessel imaging
  • nonlocal means filtering
  • Signal resolution
  • Spatial resolution
  • Spatiotemporal phenomena
  • Super-resolution imaging
  • Ultrasonic imaging

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering

Cite this

@article{24079b14e7e543dbada11732b7e173d2,
title = "Improved Super-Resolution Ultrasound Microvessel Imaging with Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking",
abstract = "Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This study aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high frame rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this study, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-section profile with full width at half maximum of 57 μm could be imaged at approximately 2 cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution ~200 μm). Cortical microvessels that are 76 μm apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.",
keywords = "bipartite graph, contrast microbubbles, Filtering, Imaging, microbubble tracking, microvessel imaging, nonlocal means filtering, Signal resolution, Spatial resolution, Spatiotemporal phenomena, Super-resolution imaging, Ultrasonic imaging",
author = "Pengfei Song and Trazasko, {Joshua D} and Armando Manduca and Runqing Huang and Kadirvel, {Ramanathan D} and Kallmes, {David F} and Chen, {Shigao D}",
year = "2017",
month = "11",
day = "29",
doi = "10.1109/TUFFC.2017.2778941",
language = "English (US)",
journal = "IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control",
issn = "0885-3010",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Improved Super-Resolution Ultrasound Microvessel Imaging with Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking

AU - Song, Pengfei

AU - Trazasko, Joshua D

AU - Manduca, Armando

AU - Huang, Runqing

AU - Kadirvel, Ramanathan D

AU - Kallmes, David F

AU - Chen, Shigao D

PY - 2017/11/29

Y1 - 2017/11/29

N2 - Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This study aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high frame rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this study, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-section profile with full width at half maximum of 57 μm could be imaged at approximately 2 cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution ~200 μm). Cortical microvessels that are 76 μm apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.

AB - Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This study aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high frame rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this study, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-section profile with full width at half maximum of 57 μm could be imaged at approximately 2 cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution ~200 μm). Cortical microvessels that are 76 μm apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.

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KW - Ultrasonic imaging

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