Carotid Artery and Jugular Vein Tracking and Differentiation Using Spatiotemporal Analysis

  • David Wang
  • Roberta Klatzky
  • Nikhil Amesur
  • George Stetten
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)


We have derived and evaluated parameters from ultrasound images of the neck to permit a computer to automatically characterize and differentiate between the carotid artery and jugular vein at image acquisition time during vascular interventions, given manually placed seed points. Our goal is to prevent inadvertent damage to the carotid artery when targeting the jugular vein for catheterization. We used a portable 10 MHz ultrasound system to acquire cross sectional B-mode ultrasound images of these great vessels at 10 fps. An expert user identified the vessels in the first frame by touching the vessels on the screen with his fingertip, and the computer automatically tracked the vessels and calculated a best-fit ellipse for each vessel in each subsequent frame. Vessel location and radii were further analyzed to produce parameters that proved useful for differentiating between the carotid artery and jugular vein. These parameters include relative location of the vessels, distension of the vessel walls, and consistent phase difference between the arterial and venous pulsations as determined by temporal Fourier analysis.


Carotid Artery Jugular Vein Internal Jugular Vein Manual Tracing Internal Jugular Vein Cannulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • David Wang
    • 1
    • 2
  • Roberta Klatzky
    • 1
  • Nikhil Amesur
    • 2
  • George Stetten
    • 1
    • 2
  1. 1.Carnegie Mellon UniversityPittsburghUSA
  2. 2.University of Pittsburgh Medical CenterPittsburghUSA

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