Purchase this article with an account.
R. Theodore Smith, Jan P. Koniarek, Jackie Chan, Takayuki Nagasaki, Janet R. Sparrow, Kevin Langton; Autofluorescence Characteristics of Normal Foveas and Reconstruction of Foveal Autofluorescence from Limited Data Subsets. Invest. Ophthalmol. Vis. Sci. 2005;46(8):2940-2946. doi: https://doi.org/10.1167/iovs.04-0778.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
purpose. To develop mathematical and geometric models of the nonuniform autofluorescence (AF) patterns of foveas of normal subjects and to reconstruct these models from limited subsets of data.
methods. Confocal scanning laser ophthalmoscope (cSLO) AF fundus images of normal maculae were obtained from both eyes of 10 middle-aged subjects. They were filtered and contrast enhanced, to obtain elliptical isobars of equal gray levels (GLs) and determine the isobars’ resolutions, eccentricities, and angles of orientation. The original image data were fit with a mathematical model of elliptic quadratic polynomials in two equal zones: the center and the remaining annulus.
results. The AF images segmented into nested concentric GL isobars with GLs that increased radially from the least-fluorescent center. The mean isobar resolution was 31 ± 7 μm. The geometric eccentricity of the ellipses increased from 0.42 ± 0.12 centrally to 0.52 ± 0.14 peripherally (P = 0.0005), with mean axes of orientation peripherally 97.12 ± 15.46°. The model fits to the complete image data had mean absolute normalized errors ranging from 3.6% ± 3.7% to 7.3% ± 7.1%. The model fits to small subsets (1% to 2% of total image data) had mean absolute errors ranging from 3.7% ± 3.8% to 7.3% ± 7.2%.
conclusions. Normal AF fundus images show finely resolved, concentric, elliptical foveal patterns consistent with the anatomic distribution of fluorescent lipofuscin, light-attenuating macular pigment (MP), cone photopigment, and retinal pigment epithelial (RPE) pigment in the fovea. A two-zone, elliptic, quadratic polynomial model can accurately model foveal data. This model may be useful for image analysis and for automated segmentation of pathology.
This PDF is available to Subscribers Only