Investigation of Microbubble Detection Methods for Super-Resolution Imaging of Microvasculature

Autor: Christopher Dunsby, Kirsten Christensen-Jeffries, Jemma Brown, Robert J. Eckersley, Jiaqi Zhu, Ge Zhang, Meng-Xing Tang, Sevan Harput
Přispěvatelé: Engineering & Physical Science Research Council (EPSRC)
Rok vydání: 2019
Předmět:
Technology
Acoustics and Ultrasonics
PROPAGATION
01 natural sciences
ANGIOGENESIS
09 Engineering
030218 nuclear medicine & medical imaging
Engineering
0302 clinical medicine
SIZE DISTRIBUTION
Image Processing
Computer-Assisted
super-localization
010301 acoustics
Instrumentation
Image resolution
Ultrasonography
Physics
02 Physical Sciences
Microbubbles
Phantoms
Imaging
Bandwidth (signal processing)
DOPPLER
Transducer
symbols
Doppler effect
Algorithms
Acoustics
Transducers
Image processing
Low frequency
FREQUENCY
Models
Biological
03 medical and health sciences
symbols.namesake
Detection methods
0103 physical sciences
Singular value decomposition
Computer Simulation
Electrical and Electronic Engineering
AGENTS
Science & Technology
Engineering
Electrical & Electronic
QUANTIFICATION
Nonlinear system
RESOLUTION
Microvessels
CONTRAST-ENHANCED ULTRASOUND
microbubbles (MBs)
super-resolution imaging
Zdroj: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 66:676-691
ISSN: 1525-8955
0885-3010
DOI: 10.1109/tuffc.2019.2894755
Popis: Ultrasound super-resolution techniques use the response of microbubble contrast agents (MBs) to visualize the microvasculature. Techniques that localize isolated bubble signals first require detection algorithms to separate the MB and tissue responses. This work explores the three main MB detection techniques for super-resolution of microvasculature. Pulse inversion (PI), differential imaging (DI) and singular value decomposition (SVD) filtering were compared in terms of the localization accuracy, precision and contrast to tissue ratio (CTR). MB responses were simulated based on the properties of Sonovue™ and using the Marmottant model. Non-linear propagation through tissue was modelled using the k-Wave software package. For the parameters studied, the results show that PI is most appropriate for low frequency applications, but also most dependent on transducer bandwidth. SVD is preferable for high frequency acquisition where localization precision on the order of a few microns is possible. PI is largely independent of flow direction and speed compared to SVD and DI, so is appropriate for visualizing the slowest flows and tortuous vasculature. SVD is unsuitable for stationary MBs and can introduce a localization error on the order of hundreds of microns over the speed range 0- 2 mm/s and flow directions from lateral (parallel to probe) to axial (perpendicular to probe). DI is only suitable for flow rates > 0.5 mm/s or as flow becomes more axial. Overall, this study develops a MB and tissue non-linear simulation platform to improve understanding of how different MB detection techniques can impact the super-resolution process and explores some of the factors influencing the suitability of each.
Databáze: OpenAIRE
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