Application of maximum-likelihood estimation in optical coherence tomography for nanometer-class thickness estimation

Jinxin Huang; Qun Yuan; Patrice Tankam; Eric Clarkson; Matthew Kupinski; Holly B. Hindman; James V. Aquavella; Jannick P. Rolland

doi:10.1117/12.2083160

5 March 2015 Application of maximum-likelihood estimation in optical coherence tomography for nanometer-class thickness estimation

Jinxin Huang, Qun Yuan, Patrice Tankam, Eric Clarkson, Matthew Kupinski, Holly B. Hindman, James V. Aquavella, Jannick P. Rolland

Author Affiliations +

Proceedings Volume 9315, Design and Quality for Biomedical Technologies VIII; 93150F (2015) https://doi.org/10.1117/12.2083160
Event: SPIE BiOS, 2015, San Francisco, California, United States

Abstract

In biophotonics imaging, one important and quantitative task is layer-thickness estimation. In this study, we investigate the approach of combining optical coherence tomography and a maximum-likelihood (ML) estimator for layer thickness estimation in the context of tear film imaging. The motivation of this study is to extend our understanding of tear film dynamics, which is the prerequisite to advance the management of Dry Eye Disease, through the simultaneous estimation of the thickness of the tear film lipid and aqueous layers. The estimator takes into account the different statistical processes associated with the imaging chain. We theoretically investigated the impact of key system parameters, such as the axial point spread functions (PSF) and various sources of noise on measurement uncertainty. Simulations show that an OCT system with a 1 μm axial PSF (FWHM) allows unbiased estimates down to nanometers with nanometer precision. In implementation, we built a customized Fourier domain OCT system that operates in the 600 to 1000 nm spectral window and achieves 0.93 micron axial PSF in corneal epithelium. We then validated the theoretical framework with physical phantoms made of custom optical coatings, with layer thicknesses from tens of nanometers to microns. Results demonstrate unbiased nanometer-class thickness estimates in three different physical phantoms.

Citation Download Citation

Jinxin Huang, Qun Yuan, Patrice Tankam, Eric Clarkson, Matthew Kupinski, Holly B. Hindman, James V. Aquavella, and Jannick P. Rolland "Application of maximum-likelihood estimation in optical coherence tomography for nanometer-class thickness estimation", Proc. SPIE 9315, Design and Quality for Biomedical Technologies VIII, 93150F (5 March 2015); https://doi.org/10.1117/12.2083160

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Optical coherence tomography

Point spread functions

Refractive index

Mirrors

Coating

Eye

Interfaces

Show All Keywords

Keywords/Phrases

Search In:

Publication Years