{"id":{"repo_id":"auckland-ms","oai_identifier":"oai:researchspace.auckland.ac.nz:2292/69306"},"canonical_url":"https://search.dev.ndltd.org/etd/auckland-ms/oai:researchspace.auckland.ac.nz:2292/69306","repository":{"repo_id":"auckland-ms","name":"University of Auckland","base_url":"https://researchspace.auckland.ac.nz/server/oai/request"},"display":{"title":"Optical coherence tomography: Development of functional extension and algorithms tailored to biomedical applications","abstract":"Optical Coherence Tomography (OCT) enables real-time, non-contact and high-resolution structural depth imaging of semi-transparent objects. As a result, OCT plays an essential role in biomedical studies as well as in routine medical examinations, such as of the eyes or skin diagnostics. In addition to OCT’s unique imaging capabilities, it can be used to retrieve functional information from samples. Functional information includes quantitative optical parameters that describe light refraction, attenuation, scattering, and dispersion phenomena. Despite a number of different studies conducted using OCT-derived functional information, there is still a research gap in functional information retrieval and utilisation approaches, especially in the biomedical field. The aim of this thesis is to introduce novel approaches based on a combination of structural and functional information to increase the abilities of OCT imaging techniques. This study included the development of a custom-built supercontinuum laser-based spectral-domain OCT (SD-OCT) system. The custom design contains a hardware extension for extended depth-imaging capabilities. The broadband bandwidth of a supercontinuum source provides the ability to retrieve spectral-dependant functional information from the sample. We demonstrate post-processing algorithms to retrieve functional information using the SD-OCT signal, which can be used in particle size estimation algorithms or cancerous cell characterisation. Furthermore, we demonstrate implementation of functional information with machine learning techniques for classification based on morphological differences. This classification technique can be used for further cancer research.","abstract_html":"Optical Coherence Tomography (OCT) enables real-time, non-contact and high-resolution structural depth imaging of semi-transparent objects. As a result, OCT plays an essential role in biomedical studies as well as in routine medical examinations, such as of the eyes or skin diagnostics. In addition to OCT’s unique imaging capabilities, it can be used to retrieve functional information from samples. Functional information includes quantitative optical parameters that describe light refraction, attenuation, scattering, and dispersion phenomena. Despite a number of different studies conducted using OCT-derived functional information, there is still a research gap in functional information retrieval and utilisation approaches, especially in the biomedical field. The aim of this thesis is to introduce novel approaches based on a combination of structural and functional information to increase the abilities of OCT imaging techniques. This study included the development of a custom-built supercontinuum laser-based spectral-domain OCT (SD-OCT) system. The custom design contains a hardware extension for extended depth-imaging capabilities. The broadband bandwidth of a supercontinuum source provides the ability to retrieve spectral-dependant functional information from the sample. We demonstrate post-processing algorithms to retrieve functional information using the SD-OCT signal, which can be used in particle size estimation algorithms or cancerous cell characterisation. Furthermore, we demonstrate implementation of functional information with machine learning techniques for classification based on morphological differences. This classification technique can be used for further cancer research.","abstract_has_math":false,"creators":["Zlygostiev, Mykola"],"institution":"ResearchSpace@Auckland","degree_name":"PhD","degree_level":"Doctoral","degree_discipline":"Physics","degree_department":null,"school":null,"contributors":[],"advisors":["Vanholsbeeck, Frederique","McGoverin, Cushla","Bonesi, Marco"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022","date_published":"2022","updated_at":"2026-07-24T01:03:18Z","subjects":[],"languages":[],"rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"rights_urls":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2292/69306","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Vanholsbeeck, Frederique","McGoverin, Cushla","Bonesi, Marco"]},{"key":"dc:creator","label":"Author","values":["Zlygostiev, Mykola"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-07-21T20:17:09Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-07-21T20:17:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2022"]},{"key":"dc:publisher","label":"Institution","values":["ResearchSpace@Auckland"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Physics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["PhD"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Auckland"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2292/69306"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Optical Coherence Tomography (OCT) enables real-time, non-contact and high-resolution structural depth imaging of semi-transparent objects. As a result, OCT plays an essential role in biomedical studies as well as in routine medical examinations, such as of the eyes or skin diagnostics. In addition to OCT’s unique imaging capabilities, it can be used to retrieve functional information from samples. Functional information includes quantitative optical parameters that describe light refraction, attenuation, scattering, and dispersion phenomena. Despite a number of different studies conducted using OCT-derived functional information, there is still a research gap in functional information retrieval and utilisation approaches, especially in the biomedical field. The aim of this thesis is to introduce novel approaches based on a combination of structural and functional information to increase the abilities of OCT imaging techniques. This study included the development of a custom-built supercontinuum laser-based spectral-domain OCT (SD-OCT) system. The custom design contains a hardware extension for extended depth-imaging capabilities. The broadband bandwidth of a supercontinuum source provides the ability to retrieve spectral-dependant functional information from the sample. We demonstrate post-processing algorithms to retrieve functional information using the SD-OCT signal, which can be used in particle size estimation algorithms or cancerous cell characterisation. Furthermore, we demonstrate implementation of functional information with machine learning techniques for classification based on morphological differences. This classification technique can be used for further cancer research."]},{"key":"dc:title","label":"Title","values":["Optical coherence tomography: Development of functional extension and algorithms tailored to biomedical applications"]}]}],"canonical_facts":{"dc:contributor.advisor":["Vanholsbeeck, Frederique","McGoverin, Cushla","Bonesi, Marco"],"dc:creator":["Zlygostiev, Mykola"],"dc:date.accessioned":["2024-07-21T20:17:09Z"],"dc:date.available":["2024-07-21T20:17:09Z"],"dc:date.issued":["2022"],"dc:description.abstract":["Optical Coherence Tomography (OCT) enables real-time, non-contact and high-resolution structural depth imaging of semi-transparent objects. As a result, OCT plays an essential role in biomedical studies as well as in routine medical examinations, such as of the eyes or skin diagnostics. In addition to OCT’s unique imaging capabilities, it can be used to retrieve functional information from samples. Functional information includes quantitative optical parameters that describe light refraction, attenuation, scattering, and dispersion phenomena. Despite a number of different studies conducted using OCT-derived functional information, there is still a research gap in functional information retrieval and utilisation approaches, especially in the biomedical field. The aim of this thesis is to introduce novel approaches based on a combination of structural and functional information to increase the abilities of OCT imaging techniques. This study included the development of a custom-built supercontinuum laser-based spectral-domain OCT (SD-OCT) system. The custom design contains a hardware extension for extended depth-imaging capabilities. The broadband bandwidth of a supercontinuum source provides the ability to retrieve spectral-dependant functional information from the sample. We demonstrate post-processing algorithms to retrieve functional information using the SD-OCT signal, which can be used in particle size estimation algorithms or cancerous cell characterisation. Furthermore, we demonstrate implementation of functional information with machine learning techniques for classification based on morphological differences. This classification technique can be used for further cancer research."],"dc:identifier.uri":["https://hdl.handle.net/2292/69306"],"dc:publisher":["ResearchSpace@Auckland"],"dc:rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"dc:rights.uri":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"dc:title":["Optical coherence tomography: Development of functional extension and algorithms tailored to biomedical applications"],"dc:type":["Thesis"],"thesis:degree_discipline":["Physics"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["PhD"],"thesis:institution_name":["The University of Auckland"]},"updated_at":"2026-07-24T01:03:18Z"}