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Real-Time GPU Implementation of Transverse Oscillation Vector Velocity Flow Imaging

David Pierson Bradway, Michael Johannes Pihl, Andreas Krebs, Borislav Gueorguiev Tomov, Carsten Straso Kjaer, Svetoslav Ivanov Nikolov, Jorgen Arendt Jensen
Center for Fast Ultrasound Imaging, Biomedical Engineering Group, Department of Electrical Engineering, Orsteds Plads Building 349, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
SPIE Medical Imaging, 2014

@inbook{bradway2014real,

   title={"Real-TimeGPUImplementationofTransverseOscillationVectorVelocityFlowImaging"},

   publisher={"SPIE-InternationalSocietyforOpticalEngineering"},

   author={"DavidBradwayandPihl},

   year={2014},

   booktitle={Proceedings of SPIE Medical Imaging 2014}

}

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Rapid estimation of blood velocity and visualization of complex flow patterns are important for clinical use of diagnostic ultrasound. This paper presents real-time processing for two-dimensional (2-D) vector flow imaging which utilizes an off-the-shelf graphics processing unit (GPU). In this work, Open Computing Language (OpenCL) is used to estimate 2-D vector velocity flow in vivo in the carotid artery. Data are streamed live from a BK Medical 2202 Pro Focus UltraView Scanner to a workstation running a research interface software platform. Processing data from a 50 millisecond frame of a duplex vector flow acquisition takes 2.3 milliseconds seconds on an Advanced Micro Devices Radeon HD 7850 GPU card. The detected velocities are accurate to within the precision limit of the output format of the display routine. Because this tool was developed as a module external to the scanner’s built-in processing, it enables new opportunities for prototyping novel algorithms, optimizing processing parameters, and accelerating the path from development lab to clinic.
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