Computational and Hardware Adaptive Optics for Biomedical Imaging with Optical Coherence Tomography

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Optical coherence tomography (OCT) is an emerging technology that enables volumetric imaging of biological samples. OCT has several advantages over other imaging modalities, including parallel depth acquisition, access to complex optical field and label free. Optical coherence microscopy (OCM) is a higher-transverse-resolution version of OCT.The basic science applications of OCT and OCM are expanding, and one important application area involves imaging in the rat and mouse brain. However, there are several challenges for current biomedical application of OCT/OCM. The first challenge is the compromise between lateral resolution and depth-of-field (DOF), which has limited the volumetric imaging throughput of OCT. Another challenge is related to the multiple scattering (MS) in the biological sample, which severely limits the imaging depth of an OCT system. In this dissertation, I will first present volumetric OCM of mouse brain ex vivo with a large depth coverage by leveraging computational adaptive optics (CAO) to significantly reduce the number of OCM volumes that need to be acquired with a Gaussian beam focused at different depths. I will also present a space/spatial-frequency domain analysis framework for the investigation of MS in OCT, and apply the framework to compare aberration-diverse optical coherence tomography (AD-OCT), a previously published technique for MS suppression, to standard Gaussian-beam OCT via experiments in scattering tissue phantoms. Besides that, a theoretical study will be presented to study the transverse point-spread function (PSF) in presence of MS and investigate the effect of different factors on the MS suppression performance provided by AD-OCT.
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156 pages
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Adie, Steven Graham
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Xu, Chris
Warden, Melissa
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Biomedical Engineering
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Ph. D., Biomedical Engineering
Degree Level
Doctor of Philosophy
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Government Document
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dissertation or thesis
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