Open Access
6 January 2021 Multi-reference global registration of individual A-lines in adaptive optics optical coherence tomography retinal images
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Abstract

Significance: Adaptive optics optical coherence tomography (AO-OCT) technology enables non-invasive, high-resolution three-dimensional (3D) imaging of the retina and promises earlier detection of ocular disease. However, AO-OCT data are corrupted by eye-movement artifacts that must be removed in post-processing, a process rendered time-consuming by the immense quantity of data.

Aim: To efficiently remove eye-movement artifacts at the level of individual A-lines, including those present in any individual reference volume.

Approach: We developed a registration method that cascades (1) a 3D B-scan registration algorithm with (2) a global A-line registration algorithm for correcting torsional eye movements and image scaling and generating global motion-free coordinates. The first algorithm corrects 3D translational eye movements to a single reference volume, accelerated using parallel computing. The second algorithm combines outputs of multiple runs of the first algorithm using different reference volumes followed by an affine transformation, permitting registration of all images to a global coordinate system at the level of individual A-lines.

Results: The 3D B-scan algorithm estimates and corrects 3D translational motions with high registration accuracy and robustness, even for volumes containing microsaccades. Averaging registered volumes improves our image quality metrics up to 22 dB. Implementation in CUDA™ on a graphics processing unit registers a 512  ×  512  ×  512 volume in only 10.6 s, 150 times faster than MATLAB™ on a central processing unit. The global A-line algorithm minimizes image distortion, improves regularity of the cone photoreceptor mosaic, and supports enhanced visualization of low-contrast retinal cellular features. Averaging registered volumes improves our image quality up to 9.4 dB. It also permits extending the imaging field of view (∼2.1  ×  ) and depth of focus (∼5.6  ×  ) beyond what is attainable with single-reference registration.

Conclusions: We can efficiently correct eye motion in all 3D at the level of individual A-lines using a global coordinate system.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Kazuhiro Kurokawa, James A. Crowell, Nhan Do, John J. Lee, and Donald T. Miller "Multi-reference global registration of individual A-lines in adaptive optics optical coherence tomography retinal images," Journal of Biomedical Optics 26(1), 016001 (6 January 2021). https://doi.org/10.1117/1.JBO.26.1.016001
Received: 21 August 2020; Accepted: 10 December 2020; Published: 6 January 2021
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Image registration

Eye

Adaptive optics optical coherence tomography

3D acquisition

Cones

Detection and tracking algorithms

Video

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