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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 2 of 2 (0.03 seconds)Spelling suggestions: "subject:"eye -- homography"" "subject:"eye -- lomography""
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Segmentation of human retinal layers from optical coherence tomography scansHammes, Nathan M. 09 February 2015 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / An algorithm was developed in to efficiently segment the inner-limiting membrane (ILM) and retinal pigmented epithelium (RPE) from spectral domain-optical coherence tomography image volumes. A deformable model framework is described and implemented in which free-form deformations (FFD) are used to direct two deformable sheets to the two high-contrast layers of interest. Improved accuracy in determining retinal thickness (the distance between the ILM and the RPE) is demonstrated against the commercial state-of-the-art Spectralis OCT native segmentation software. A novel adaptation of the highest confidence first (HCF) algorithm is utilized to improve upon the initial results. The proposed adaptation of HCF provides distance-based clique potentials and an efficient solution to layer-based segmentation, reducing a 3D problem to 2D inference.
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Real-time adaptive-optics optical coherence tomography (AOOCT) image reconstruction on a GPUShafer, Brandon Andrew January 2014 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Adaptive-optics optical coherence tomography (AOOCT) is a technology that has been rapidly advancing in recent years and offers amazing capabilities in scanning the human eye in vivo. In order to bring the ultra-high resolution capabilities to clinical use, however, newer technology needs to be used in the image reconstruction process. General purpose computation on graphics processing units is one such way that this computationally intensive reconstruction can be performed in a desktop computer in real-time. This work shows the process of AOOCT image reconstruction, the basics of how to use NVIDIA's CUDA to write parallel code, and a new AOOCT image reconstruction technology implemented using NVIDIA's CUDA. The results of this work demonstrate that image reconstruction can be done in real-time with high accuracy using a GPU.
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