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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 10 — Oct. 1, 2013
  • pp: 1806–1816

Maximum-likelihood estimation in Optical Coherence Tomography in the context of the tear film dynamics

Jinxin Huang, Eric Clarkson, Matthew Kupinski, Kye-sung Lee, Kara L. Maki, David S. Ross, James V. Aquavella, and Jannick P. Rolland  »View Author Affiliations

Biomedical Optics Express, Vol. 4, Issue 10, pp. 1806-1816 (2013)

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Understanding tear film dynamics is a prerequisite for advancing the management of Dry Eye Disease (DED). In this paper, we discuss the use of optical coherence tomography (OCT) and statistical decision theory to analyze the tear film dynamics of a digital phantom. We implement a maximum-likelihood (ML) estimator to interpret OCT data based on mathematical models of Fourier-Domain OCT and the tear film. With the methodology of task-based assessment, we quantify the tradeoffs among key imaging system parameters. We find, on the assumption that the broadband light source is characterized by circular Gaussian statistics, ML estimates of 40 nm +/− 4 nm for an axial resolution of 1 μm and an integration time of 5 μs. Finally, the estimator is validated with a digital phantom of tear film dynamics, which reveals estimates of nanometer precision.

© 2013 OSA

OCIS Codes
(030.0030) Coherence and statistical optics : Coherence and statistical optics
(110.3000) Imaging systems : Image quality assessment

ToC Category:
Ophthalmology Applications

Original Manuscript: June 10, 2013
Revised Manuscript: August 17, 2013
Manuscript Accepted: August 17, 2013
Published: August 29, 2013

Jinxin Huang, Eric Clarkson, Matthew Kupinski, Kye-sung Lee, Kara L. Maki, David S. Ross, James V. Aquavella, and Jannick P. Rolland, "Maximum-likelihood estimation in Optical Coherence Tomography in the context of the tear film dynamics," Biomed. Opt. Express 4, 1806-1816 (2013)

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