Presentation
13 March 2024 Computational approach to correcting defocus in human corneal images acquired with Powell lens line-field OCT
Author Affiliations +
Proceedings Volume PC12824, Ophthalmic Technologies XXXIV; PC128240X (2024) https://doi.org/10.1117/12.3005888
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
This study presents a novel method for correcting aberrations and diffraction-induced artifacts in optical coherence tomography (OCT) images. The method takes advantage of light backpropagation models in combination with non-stationary despeckling and sharpness optimization algorithms to improve the overall quality of OCT images. The algorithm's application to the eye data acquired using a Powell Lens-based Line-Field OCT (PL-LF-OCT) system with a high numerical aperture (NA) and short depth-of-focus (DOF) resulted in significant enhancements in images captured at different depths. This promising improvement signifies the potential for providing ultra-high resolution volumetric OCT data without the need for depth scanning.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Nima Abbasi Firoozjah, Keyu Chen, Alexander Wong, and Kostadinka Bizheva "Computational approach to correcting defocus in human corneal images acquired with Powell lens line-field OCT", Proc. SPIE PC12824, Ophthalmic Technologies XXXIV, PC128240X (13 March 2024); https://doi.org/10.1117/12.3005888
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KEYWORDS
Optical coherence tomography

Depth of field

Algorithm development

Image quality

Optical limiting

Optical design

Optical imaging

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