Automated computational aberration correction method for OCT and OCM (Conference Presentation)

Yuan-Zhi Liu; Paritosh Pande; Fredrick A. South; Stephen A. Boppart

doi:10.1117/12.2251514

19 April 2017 Automated computational aberration correction method for OCT and OCM (Conference Presentation)

Yuan-Zhi Liu, Paritosh Pande, Fredrick A. South, Stephen A. Boppart

Proceedings Volume 10053, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXI; 100530V (2017) https://doi.org/10.1117/12.2251514
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Aberrations in an optical system cause a reduction in imaging resolution and poor image contrast, and limit the imaging depth when imaging biological samples. Computational adaptive optics (CAO) provides an inexpensive and simpler alternative to the traditionally used hardware-based adaptive optics (HAO) techniques. In this paper, we present an automated computational aberration correction method for broadband interferometric imaging techniques, e.g. optical coherence tomography (OCT) and optical coherence microscopy (OCM). In the proposed method, the process of aberration correction is modeled as a filtering operation on the aberrant image using a phase filter in the Fourier domain. The phase filter is expressed as a linear combination of Zernike polynomials with unknown coefficients, which are estimated through an iterative optimization scheme based on maximizing an image sharpness metric. The Resilient backpropagation (Rprop) algorithm, which was originally proposed as an alternative to the gradient-descent-based backpropagation algorithm for training the weights in a multilayer feedforward neural network, is employed to optimize the Zernike polynomial coefficients because of its simplicity and the robust performance to the choice of various parameters. Stochastic selection of the number and type of Zernike modes is introduced at each optimization step to explore different trajectories to enable search for multiple optima in the multivariate search space. The method was validated on various tissue samples and shows robust performance for samples with different scattering properties, e.g. a phantom with subresolution particles, an ex vivo rabbit adipose tissue, and an in vivo photoreceptor layer of the human retina.

Conference Presentation

Citation Download Citation

Yuan-Zhi Liu, Paritosh Pande, Fredrick A. South, and Stephen A. Boppart "Automated computational aberration correction method for OCT and OCM (Conference Presentation)", Proc. SPIE 10053, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXI, 100530V (19 April 2017); https://doi.org/10.1117/12.2251514

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
PRESENTATION

WATCH
PRESENTATION SAVE TO MY LIBRARY

GET CITATION

KEYWORDS

Optical coherence tomography

Aberration correction

Image filtering

Imaging systems

Tissue optics

Adaptive optics

Evolutionary algorithms

Show All Keywords

Keywords/Phrases

Search In:

Publication Years