Thickness estimation with optical coherence tomography and statistical decision theory

Jinxin Huang; Eric Clarkson; Matthew Kupinski; Jannick P. Rolland

doi:10.1364/sumsession.2013.tu9

Thickness estimation with optical coherence tomography and statistical decision theory

Jinxin Huang, Eric Clarkson, Matthew Kupinski, Jannick P. Rolland

Research output: Contribution to journal › Conference article › peer-review

Abstract

We implement a maximum-likelihood (ML) estimator to interpret Optical Coherence Tomography (OCT) data, based on a Fourier-Domain OCT and a two-interface tear film model. We use the root mean square error as a figure of merit to quantify the system performance to estimate the tear film thickness. The impact of detector integration time is quantified. For an OCT system with a 1 μm axial resolution, the ML estimator can estimate up to 40 nm with a 10% relative error.

Original language	English (US)
Pages (from-to)	49-51
Number of pages	3
Journal	Optics InfoBase Conference Papers
DOIs	https://doi.org/10.1364/sumsession.2013.tu9
State	Published - 2013
Event	CIOMP-OSA Summer Session on Optical Engineering, Design and Manufacturing, SumSession_OEDM 2013 - Changchun, China Duration: Aug 4 2013 → Aug 9 2013

ASJC Scopus subject areas

Instrumentation
Atomic and Molecular Physics, and Optics

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10.1364/sumsession.2013.tu9

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title = "Thickness estimation with optical coherence tomography and statistical decision theory",

abstract = "We implement a maximum-likelihood (ML) estimator to interpret Optical Coherence Tomography (OCT) data, based on a Fourier-Domain OCT and a two-interface tear film model. We use the root mean square error as a figure of merit to quantify the system performance to estimate the tear film thickness. The impact of detector integration time is quantified. For an OCT system with a 1 μm axial resolution, the ML estimator can estimate up to 40 nm with a 10% relative error.",

author = "Jinxin Huang and Eric Clarkson and Matthew Kupinski and Rolland, {Jannick P.}",

year = "2013",

doi = "10.1364/sumsession.2013.tu9",

language = "English (US)",

pages = "49--51",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

note = "CIOMP-OSA Summer Session on Optical Engineering, Design and Manufacturing, SumSession_OEDM 2013 ; Conference date: 04-08-2013 Through 09-08-2013",

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TY - JOUR

T1 - Thickness estimation with optical coherence tomography and statistical decision theory

AU - Huang, Jinxin

AU - Clarkson, Eric

AU - Kupinski, Matthew

AU - Rolland, Jannick P.

PY - 2013

Y1 - 2013

N2 - We implement a maximum-likelihood (ML) estimator to interpret Optical Coherence Tomography (OCT) data, based on a Fourier-Domain OCT and a two-interface tear film model. We use the root mean square error as a figure of merit to quantify the system performance to estimate the tear film thickness. The impact of detector integration time is quantified. For an OCT system with a 1 μm axial resolution, the ML estimator can estimate up to 40 nm with a 10% relative error.

AB - We implement a maximum-likelihood (ML) estimator to interpret Optical Coherence Tomography (OCT) data, based on a Fourier-Domain OCT and a two-interface tear film model. We use the root mean square error as a figure of merit to quantify the system performance to estimate the tear film thickness. The impact of detector integration time is quantified. For an OCT system with a 1 μm axial resolution, the ML estimator can estimate up to 40 nm with a 10% relative error.

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U2 - 10.1364/sumsession.2013.tu9

DO - 10.1364/sumsession.2013.tu9

M3 - Conference article

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SP - 49

EP - 51

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

SN - 2162-2701

T2 - CIOMP-OSA Summer Session on Optical Engineering, Design and Manufacturing, SumSession_OEDM 2013

Y2 - 4 August 2013 through 9 August 2013

ER -

Thickness estimation with optical coherence tomography and statistical decision theory

Abstract

ASJC Scopus subject areas

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