Optical designs and image processing algorithms for optical coherence tomography detection of glaucoma
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Optical Coherence Tomography (OCT) is an optical tomography technique which provides high resolution non-invasive three-dimensional (3D) structural images of the sample based on coherent properties of light. The dissertation focuses on the use of OCT systems for detecting glaucoma, which is the second leading cause of blindness worldwide. First, as a prerequisite of analyzing ophthalmologic OCT images, a retinal sublayer segmentation algorithm is presented and implemented with GPU assisted computation. Then, a polarization-sensitive optical coherence tomography (PS-OCT) system was constructed for the study of glaucoma. Three closely related clinical and animal studies on early-stage glaucoma detection using either OCT or PS-OCT were performed. Statistical analysis of the study results indicates that the scattering property of retinal nerve fiber layer (RNFL) is the earliest indicator for glaucoma. Finally, to investigate the scattering properties of RNFL, a pathlength-multiplexed scattering-angle-diverse optical coherence tomography (PM-SAD-OCT) system was designed and built. PM-SAD-OCT images were collected from human and rodent retina as well as earthworm nerve cord. PM-SAD-OCT system shows promising potentials to detect neurodegenerative diseases including glaucoma.