{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/73084"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/73084","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Model-based quantitative combinatorial optical microscopy for extracting clinical imaging biomarkers","abstract":"In recent years, many noninvasive, high-resolution biomedical optical imaging techniques based on unique, yet complementary, contrast mechanisms have emerged. While each imaging modality is able to elucidate certain properties of the particular sample under study, an integrated approach in which all modalities are acquired in a simultaneous, co-registered manner can prove advantageous in obtaining a more complete understanding of the sample under study. While this multimodal approach to biomedical imaging is beginning to find more widespread use, thus far most applications of these techniques have been purely qualitative, ignoring the incredibly dense, multidimensional datasets acquired. This thesis presents the framework and several applications of a quantitative model-based combinatorial analysis method. The analysis technique developed provides a direct link between multimodal image contrast and physiological biomarkers. Applications include identification of tissue constituents in fixed tissue slices and classification of cell death mechanisms in a living engineered tissue sample.","abstract_html":"In recent years, many noninvasive, high-resolution biomedical optical imaging techniques based on unique, yet complementary, contrast mechanisms have emerged. While each imaging modality is able to elucidate certain properties of the particular sample under study, an integrated approach in which all modalities are acquired in a simultaneous, co-registered manner can prove advantageous in obtaining a more complete understanding of the sample under study. While this multimodal approach to biomedical imaging is beginning to find more widespread use, thus far most applications of these techniques have been purely qualitative, ignoring the incredibly dense, multidimensional datasets acquired. This thesis presents the framework and several applications of a quantitative model-based combinatorial analysis method. The analysis technique developed provides a direct link between multimodal image contrast and physiological biomarkers. Applications include identification of tissue constituents in fixed tissue slices and classification of cell death mechanisms in a living engineered tissue sample.","abstract_has_math":false,"creators":["Bower, Andrew"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Boppart, Stephen A."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-21T19:59:15Z","date_published":"2015-01-21T19:59:15Z","updated_at":"2026-07-22T22:26:07Z","subjects":["Multimodal Microscopy","Multiphoton Imaging","Image Analysis"],"languages":["en"],"rights":["Copyright 2014 Andrew Bower"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/73084","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Boppart, Stephen A."]},{"key":"dc:creator","label":"Author","values":["Bower, Andrew"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-01-21T19:59:15Z","2017-01-22T10:15:37Z","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":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["Multimodal Microscopy","Multiphoton Imaging","Image Analysis"]}]},{"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 Andrew Bower"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/73084"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In recent years, many noninvasive, high-resolution biomedical optical imaging techniques based on unique, yet complementary, contrast mechanisms have emerged. While each imaging modality is able to elucidate certain properties of the particular sample under study, an integrated approach in which all modalities are acquired in a simultaneous, co-registered manner can prove advantageous in obtaining a more complete understanding of the sample under study. While this multimodal approach to biomedical imaging is beginning to find more widespread use, thus far most applications of these techniques have been purely qualitative, ignoring the incredibly dense, multidimensional datasets acquired. This thesis presents the framework and several applications of a quantitative model-based combinatorial analysis method. The analysis technique developed provides a direct link between multimodal image contrast and physiological biomarkers. Applications include identification of tissue constituents in fixed tissue slices and classification of cell death mechanisms in a living engineered tissue sample.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2014-12-04T14:59:32Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Bower_Andrew.pdf: 9255219 bytes, checksum: 21068aaa77365fbaae719b2c78033286 (MD5)","Made available in DSpace on 2015-01-21T19:59:15Z (GMT). No. of bitstreams: 1 Andrew_Bower.pdf: 9255219 bytes, checksum: 21068aaa77365fbaae719b2c78033286 (MD5)","Embargo set by: Seth Robbins for item 73273 Lift date: 2017-01-21T19:59:39Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 73273 on 2017-01-22T10:15:37Z."]},{"key":"dc:title","label":"Title","values":["Model-based quantitative combinatorial optical microscopy for extracting clinical imaging biomarkers"]}]}],"canonical_facts":{"dc:contributor":["Boppart, Stephen A."],"dc:creator":["Bower, Andrew"],"dc:date":["2015-01-21T19:59:15Z","2017-01-22T10:15:37Z","2014-12","2015-01-21"],"dc:description":["In recent years, many noninvasive, high-resolution biomedical optical imaging techniques based on unique, yet complementary, contrast mechanisms have emerged. While each imaging modality is able to elucidate certain properties of the particular sample under study, an integrated approach in which all modalities are acquired in a simultaneous, co-registered manner can prove advantageous in obtaining a more complete understanding of the sample under study. While this multimodal approach to biomedical imaging is beginning to find more widespread use, thus far most applications of these techniques have been purely qualitative, ignoring the incredibly dense, multidimensional datasets acquired. This thesis presents the framework and several applications of a quantitative model-based combinatorial analysis method. The analysis technique developed provides a direct link between multimodal image contrast and physiological biomarkers. Applications include identification of tissue constituents in fixed tissue slices and classification of cell death mechanisms in a living engineered tissue sample.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2014-12-04T14:59:32Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Bower_Andrew.pdf: 9255219 bytes, checksum: 21068aaa77365fbaae719b2c78033286 (MD5)","Made available in DSpace on 2015-01-21T19:59:15Z (GMT). No. of bitstreams: 1 Andrew_Bower.pdf: 9255219 bytes, checksum: 21068aaa77365fbaae719b2c78033286 (MD5)","Embargo set by: Seth Robbins for item 73273 Lift date: 2017-01-21T19:59:39Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 73273 on 2017-01-22T10:15:37Z."],"dc:identifier":["http://hdl.handle.net/2142/73084"],"dc:language":["en"],"dc:rights":["Copyright 2014 Andrew Bower"],"dc:subject":["Multimodal Microscopy","Multiphoton Imaging","Image Analysis"],"dc:title":["Model-based quantitative combinatorial optical microscopy for extracting clinical imaging biomarkers"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:07Z"}