April 2010
Volume 51, Issue 13
ARVO Annual Meeting Abstract  |   April 2010
Automated and Integrated Analysis and Characterization System for Visual Field Defects in 3D
Author Affiliations & Notes
  • C. You
    Applied and Computational Mathematics, California Institute of Technology, Pasadena, California
  • W. Fink
    Visual & Autonomous Exploration Systems, Caltech, Pasadena, California
    Electrical & Computer Engineering and Biomedical Engineering, University of Arizona, Tucson, Arizona
  • Footnotes
    Commercial Relationships  C. You, None; W. Fink, Caltech patents, P.
  • Footnotes
    Support  ARO Grant W81XWH-09-1-0266
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 2335. doi:
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      C. You, W. Fink; Automated and Integrated Analysis and Characterization System for Visual Field Defects in 3D. Invest. Ophthalmol. Vis. Sci. 2010;51(13):2335.

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

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Purpose: : To introduce an automated analysis and characterization system for visual field data in three dimensions (3D).

Methods: : The 3D computer-automated threshold Amsler grid test (3D-CTAG) allows for an unprecedented characterization of the structure of visual field defects in 3D. Results of the 3D-CTAG are recorded by the computer in form of a three-dimensional data array: (x, y, contrast sensitivity(x, y)). x and y mark the location of a tested grid point in the visual field with respect to the fovea (0, 0). Contrast sensitivity(x, y) is the measured contrast sensitivity of the particular visual field location (x, y). To analyze these three-dimensional visual field data sets and to characterize the occurring visual field defects within, we have developed numerical methods that remove artifacts present in the raw data and characterize the entire visual field (visual field data transforms) and scotomas within (scotoma data transforms). Visual field data transforms comprise area and volume of visual field loss, lost and preserved area grades, and slope distribution. Scotoma data transforms comprise perimeter/scallopedness and scotoma center location.

Results: : We have created an automated and integrated analysis and characterization system, which, in the absence of clinical experts, analyzes 3D-CTAG visual field data and objectively characterizes visual field defects according to the above devised numerical methods. The output of these scotoma parameters occurs in the form of individual, appropriately documented ASCII files. Where appropriate, an automatic graphical representation, using the freely available Gnuplot graphics program, of the analysis data is generated via a Gnuplot script.

Conclusions: : The introduced automated analysis and characterization system is generically applicable to all perimetry techniques that yield a three-dimensional description of the hill-of-vision or parts thereof. The objectively derived scotoma parameters can be stored in a database and may serve as the input for an automated classification system for visual field defects, currently under development, that will probabilistically predict the ailment using statistical methods and artificial neural networks. Equipped with the above analysis package, the 3D-CTAG will be a significant step towards screening and examining people worldwide, and may assist physicians with an independent second opinion or provide expertise where otherwise not readily available.

Keywords: visual fields • neuro-ophthalmology: diagnosis • perimetry 

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