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Title:In vivo human computed optical interferometric tomography
Author(s):Shemonski, Nathan D.
Director of Research:Boppart, Stephen A.
Doctoral Committee Chair(s):Boppart, Stephen A.
Doctoral Committee Member(s):Carney, Paul S.; Bresler, Yoram; Do, Minh N.
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Optical imaging
Optical coherence tomography
In vivo imaging
Tomography
Phase filter
Motion
Stability
Deconvolution
Image reconstruction
Defocus
Aberrations
3D imaging
Abstract:This dissertation concerns the development of the fundamental theory, tools, and algorithms necessary to perform in vivo computed optical interferometric tomography. Computed imaging has made great advances in a wide variety of fields, greatly improving the diagnostic capability of each underlying imaging modality. Computed imaging techniques such as defocus and aberration correction in optical interferometric tomography, though, have remained in the research stage and have yet to become clinically-useful tools. One major challenge to be overcome for widespread acceptance is that of motion, or stability. As often noted in the literature, the most impactful potential applications for computed optical interferometric techniques involve some form of in vivo imaging. Regardless of this, the vast majority of samples imaged with computed optical interferometric tomography have been synthetic tissue mimicking phantoms, fruit samples, ex vivo tissue, or cell cultures. Not including the work presented in this dissertation, only one other example of in vivo, bulk tissue imaging has been found. In response to this disconnect of research and clinical application, this dissertation provides a framework in the form of theory, simulations, and experimental systems from which the field of in vivo computed optical interferometric tomography can advance. The framework is focused on three aspects. First are the stability requirements which provide quantitative guidelines for the type and amount of motion tolerable. Second is the stability assessment which provides techniques to quantitatively measure motion from samples and systems. Third is the correction of unstable data which broadens the possible imaging applications. Together with this framework, demonstrations of in vivo imaging over a wide range of applications including human structural skin imaging and human retinal cone photoreceptor imaging are included.
Issue Date:2015-01-21
URI:http://hdl.handle.net/2142/73035
Rights Information:Copyright 2014 Nathan Shemonski
Date Available in IDEALS:2015-01-21
Date Deposited:2014-12


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