May 2006
Volume 47, Issue 13
ARVO Annual Meeting Abstract  |   May 2006
On the Prediction of Optical Aberrations by Personalized Eye Models
Author Affiliations & Notes
  • R. Navarro
    ICMA, CSIC, Zaragoza, Spain
  • L. González
    INTA, Madrid, Spain
  • J.L. Hernández–Matamoros
    Realvision, Madrid, Spain
  • Footnotes
    Commercial Relationships  R. Navarro, None; L. González, None; J.L. Hernández–Matamoros, None.
  • Footnotes
    Support  Spanish CICyT grant FIS2005–05020–C03–01
Investigative Ophthalmology & Visual Science May 2006, Vol.47, 1186. doi:
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      R. Navarro, L. González, J.L. Hernández–Matamoros; On the Prediction of Optical Aberrations by Personalized Eye Models . Invest. Ophthalmol. Vis. Sci. 2006;47(13):1186.

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

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Purpose: : To develop and analyze a method to obtain optical models of individual eyes. Each model should reproduce the measured optical performance, in particular the monochromatic wave aberration, with high fidelity.

Methods: : First we start from a generic eye model as the input guess, and then apply a two–stage customization procedure. Stage 1 consists of replacing, in the initial generic model, those anatomical and optical parameters with experimental data measured on the eye under analysis. The set of experimental data was that provided by a standard clinical preoperative exam, namely lens topography, ultrasound biometry, and total wave aberration. Then, the second stage is to find the unknown lens geometry that would reproduce the measured wave aberration through optical optimization. Two totally different initial eye models have been compared: one considers a simpler constant refractive index for the lens, whereas the second model has a quadratic index distribution. Once we introduce the data and chose the initial generic model the customization process is automatic.

Results: : This customization method has been applied to 19 eyes with different degrees of spherical ametropia (from 0.4 D to –8 D). Two models have been obtained for each eye (constant and gradient index lens). The results were highly satisfactory, with 100% convergence, and with average RMS prediction errors about 0.006 micrometers (/100). This is one order of magnitude lower than typical measurement errors. Regarding lens geometry, the first model with a constant refractive index lens tended to overestimate surface curvatures, whereas for the second model with a quadratic index distribution we had the opposite trend, namely surfaces that were too flat.

Conclusions: : The proposed method is highly efficient and robust giving a high fidelity reproduction of the wavefront in all cases attempted so far. Limitations found in reproducing the geometry of the lens seem to be associated with the use of inaccurate models of its refractive index.

Keywords: computational modeling • optical properties 

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