April 1990
Volume 31, Issue 4
Free
Articles  |   April 1990
An image processing approach to characterizing choroidal blood flow.
Author Affiliations
  • G J Klein
    Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20707.
  • R H Baumgartner
    Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20707.
  • R W Flower
    Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20707.
Investigative Ophthalmology & Visual Science April 1990, Vol.31, 629-637. doi:
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      G J Klein, R H Baumgartner, R W Flower; An image processing approach to characterizing choroidal blood flow.. Invest. Ophthalmol. Vis. Sci. 1990;31(4):629-637.

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

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Abstract

Indocyanine green (ICG) dye angiography has made possible routine visualization of choroidal blood flow in the human eye; however, to date, its clinical utility has been limited. An overlying layer of densely pigmented tissue and the complex, multilayered vascular structure of the choroid combine to produce angiographic images of low contrast which are difficult to interpret. Conventional image processing can enhance individual images of the blood vessels, but this approach contributes no information about the dynamics of blood flow. Using relatively inexpensive, commercially available personal computer hardware, angiographic image processing algorithms were developed which appear to characterize uniquely a subject choroid in terms of various blood flow parameters. We believe this to be the first successfully demonstrated approach to routinely characterizing the human choroidal circulation in a way that conserves spatial distribution of blood flow dynamics across the entire observed choroidal area. The computer system allows acquisition of digital images from photographic film negatives; alternatively, real-time direct digitization of images from a high-resolution video camera is possible. Once acquired, the digitized data are manipulated according to various algorithms that employ time-sequence analysis to generate two-dimensional curves or three-dimensional surfaces which characterize the choroidal circulation. The unique correspondence of each three-dimensional surface to the subject choroidal circulation from which it was derived is demonstrated. Grouping the characteristic three-dimensional surfaces according to various topographic features in common may provide a basis for discriminating between normal and abnormal choroidal circulations.

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