{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/73035"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/73035","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"In vivo human computed optical interferometric tomography","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Shemonski, Nathan D."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Boppart, Stephen A.","Carney, Paul S.","Bresler, Yoram","Do, Minh N."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-21T19:58:41Z","date_published":"2015-01-21T19:58:41Z","updated_at":"2026-07-22T22:26:07Z","subjects":["Phase filter","Optical coherence tomography","In vivo imaging","Optical imaging","Tomography","Motion","Stability","Deconvolution","Image reconstruction","Defocus","Aberrations","3D imaging"],"languages":["en"],"rights":["Copyright 2014 Nathan Shemonski"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/73035","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Boppart, Stephen A.","Carney, Paul S.","Bresler, Yoram","Do, Minh N."]},{"key":"dc:creator","label":"Author","values":["Shemonski, Nathan D."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-01-21T19:58:41Z","2017-01-22T10:15:35Z","2014-12","2015-01-21"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Phase filter","Optical coherence tomography","In vivo imaging","Optical imaging","Tomography","Motion","Stability","Deconvolution","Image reconstruction","Defocus","Aberrations","3D imaging"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2014 Nathan Shemonski"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/73035"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This dissertation concerns the development of the fundamental theory, tools, and algorithms necessary to perform in vivo computed optical interferometric tomography. 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