Inverse optical design of the human eye using likelihood methods and wavefront sensing

Julia A. Sakamoto, Harrison H Barrett, Alexander V. Goncharov

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

We are developing a method for estimating patient-specific ocular parameters, including surface curvatures, conic constants, tilts, decentrations, thicknesses, refractive indices, and index gradients. The data consist of the raw detector outputs from one or more Shack-Hartmann wavefront sensors, and the parameters in the eye model are estimated by maximizing the likelihood. A Gaussian noise model is used to emulate electronic noise, so maximum likelihood reduces to nonlinear least-squares fitting between the data and the output of our optical design program. The Fisher information matrix for the Gaussian model was explored to compute bounds on the variance of the estimates for different system configurations. In this preliminary study, an accurate estimate of a chosen subset of ocular parameters was obtained using a custom search algorithm and a nearby starting point to avoid local minima in the complex likelihood surface.

Original languageEnglish (US)
Pages (from-to)304-314
Number of pages11
JournalOptics Express
Volume16
Issue number1
DOIs
StatePublished - Jan 7 2008

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Fisher information
output
estimates
random noise
set theory
estimating
curvature
refractivity
gradients
sensors
detectors
matrices
configurations
electronics

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Cite this

Inverse optical design of the human eye using likelihood methods and wavefront sensing. / Sakamoto, Julia A.; Barrett, Harrison H; Goncharov, Alexander V.

In: Optics Express, Vol. 16, No. 1, 07.01.2008, p. 304-314.

Research output: Contribution to journalArticle

Sakamoto, Julia A. ; Barrett, Harrison H ; Goncharov, Alexander V. / Inverse optical design of the human eye using likelihood methods and wavefront sensing. In: Optics Express. 2008 ; Vol. 16, No. 1. pp. 304-314.
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