Journal of Computational Neuroscience

, Volume 29, Issue 1–2, pp 5–11 | Cite as

Rapid determination of particle velocity from space-time images using the Radon transform

  • Patrick J. Drew
  • Pablo Blinder
  • Gert Cauwenberghs
  • Andy Y. Shih
  • David Kleinfeld


Laser-scanning methods are a means to observe streaming particles, such as the flow of red blood cells in a blood vessel. Typically, particle velocity is extracted from images formed from cyclically repeated line-scan data that is obtained along the center-line of the vessel; motion leads to streaks whose angle is a function of the velocity. Past methods made use of shearing or rotation of the images and a Singular Value Decomposition (SVD) to automatically estimate the average velocity in a temporal window of data. Here we present an alternative method that makes use of the Radon transform to calculate the velocity of streaming particles. We show that this method is over an order of magnitude faster than the SVD-based algorithm and is more robust to noise.


Automation Blood flow Brain Kidney Laser-scanning microscopy Line-scan tumor 



We thank Daniel N. Hill and Philbert S. Tsai for helpful discussions and two anonymous reviewers for constructive comments. This work was funded by the National Institutes of Health (EB003832, NS059832, RR021907, and MH085499 to DK; AG029681 to GC), the National Science Foundation (DBI0455027 to DK), a Bikura fellowship from the Israeli Science Foundation (to PB), and a Canadian Institute of Health post-doctoral fellowship (to AYS).


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Patrick J. Drew
    • 1
  • Pablo Blinder
    • 1
  • Gert Cauwenberghs
    • 2
    • 3
  • Andy Y. Shih
    • 1
  • David Kleinfeld
    • 1
    • 3
  1. 1.Department of PhysicsUniversity of California at San DiegoLa JollaUSA
  2. 2.Section on NeurobiologyUniversity of California at San DiegoLa JollaUSA
  3. 3.Graduate Program in NeurosciencesUniversity of California at San DiegoLa JollaUSA

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