April 2010
Volume 51, Issue 13
ARVO Annual Meeting Abstract  |   April 2010
Full-Field, Video-Based Quantitative Measurement of Retinal Blood Flow Velocity
Author Affiliations & Notes
  • D. D. Duncan
    Biomedical Engineering, Oregon Health & Science University, Portland, Oregon
  • J. Ramella-Roman
    Biomedical Engineering, Catholic University of America, Washington, Dist. of Columbia
  • Q. D. Nguyen
    Retina Division, Johns Hopkins Wilmer Eye Inst, Baltimore, Maryland
  • Footnotes
    Commercial Relationships  D.D. Duncan, None; J. Ramella-Roman, None; Q.D. Nguyen, None.
  • Footnotes
    Support  EY017577
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 4688. doi:
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    • Get Citation

      D. D. Duncan, J. Ramella-Roman, Q. D. Nguyen; Full-Field, Video-Based Quantitative Measurement of Retinal Blood Flow Velocity. Invest. Ophthalmol. Vis. Sci. 2010;51(13):4688.

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      © ARVO (1962-2015); The Authors (2016-present)

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Purpose: : The onset of diabetic retinopathy has been associated with changes in oxygen saturation and flow in retinal vessels. The objective of this study is to develop a video-based system for measuring the absolute blood flow velocity within retinal vessels as small as 12 micrometers.

Methods: : The data acquisition system is composed of a fundus ophthalmoscope, a triggered green LED, and a scientific camera. A sequence of images is acquired at a rate of 60Hz and eye motion is compensated by registering the individual images. Vessel centerlines are identified, spatial and temporal intensity variations are compensated for, and a Radon transform algorithm is used to quantify absolute centerline velocities.

Results: : We demonstrate quantitative velocity measurements in vitro and in vivo. A full noise analysis is provided so that velocity uncertainties may be quantified, and the required conditions for a velocity estimate (vessel length, diameter, number of image frames, etc) may be determined. For vessels that are fully resolved by the camera, i.e., the lumen is many pixels wide, we demonstrate recovery of velocity profiles.

Conclusions: : The system is capable of quantifying velocities from 10s of mm/sec to as low as a fraction of a mm/sec. Combined with retinal oxygenation saturation measurements, such capability provides a means of quantitatively assessing oxygen perfusion and should prove valuable in researching the etiology and management of diabetic retinopathy.

Keywords: blood supply • diabetic retinopathy 

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