{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108675"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108675","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A signal processing approach to ultrasound localization microscopy","abstract":"Ultrasound Localization Microscopy (ULM) offers a cost-effective modality for microvascular imaging by using intravascular contrast agents (microbubbles). However, ULM has a fundamental trade-off between acquisition time and spatial resolution, which makes clinical translation challenging. In this thesis, in order to circumvent the trade-off, we pose the localization problem as a signal processing problem and introduce a filtering operation that is capable of separating microbubble contrast agents into different subgroups based on their vector velocities while simultaneously offering blood velocity mapping at super resolution, without tracking individual microbubbles. We define the filtering operation in three-dimensional (3D) Fourier domain and provide rigorous theoretical analysis on the performance of the filtering operation. Numerical experiments validate that the proposed filtering method is able to separate the microbubbles with respect to the speed and direction of their motion. In combination with subsequent localization of microbubble centers, e.g. by matched filtering, velocity filter signicantly improves the quality of reconstructed vessel structure map and provides blood flow information. Overall, the proposed imaging pipeline in this thesis, eliminates the need of using diluted microbubble injections to improve image quality, thus helping to circumvent the trade-off between acquisition time and spatial resolution. Conveniently, because the velocity filtering operation can be implemented by fast Fourier transforms (FFTs) it admits fast, and potentially real-time realization. We believe that the proposed filtering method has the potential to pave the way to clinical translation of ULM.","abstract_html":"Ultrasound Localization Microscopy (ULM) offers a cost-effective modality for microvascular imaging by using intravascular contrast agents (microbubbles). However, ULM has a fundamental trade-off between acquisition time and spatial resolution, which makes clinical translation challenging. In this thesis, in order to circumvent the trade-off, we pose the localization problem as a signal processing problem and introduce a filtering operation that is capable of separating microbubble contrast agents into different subgroups based on their vector velocities while simultaneously offering blood velocity mapping at super resolution, without tracking individual microbubbles. We define the filtering operation in three-dimensional (3D) Fourier domain and provide rigorous theoretical analysis on the performance of the filtering operation. Numerical experiments validate that the proposed filtering method is able to separate the microbubbles with respect to the speed and direction of their motion. In combination with subsequent localization of microbubble centers, e.g. by matched filtering, velocity filter signicantly improves the quality of reconstructed vessel structure map and provides blood flow information. Overall, the proposed imaging pipeline in this thesis, eliminates the need of using diluted microbubble injections to improve image quality, thus helping to circumvent the trade-off between acquisition time and spatial resolution. Conveniently, because the velocity filtering operation can be implemented by fast Fourier transforms (FFTs) it admits fast, and potentially real-time realization. We believe that the proposed filtering method has the potential to pave the way to clinical translation of ULM.","abstract_has_math":false,"creators":["Soylu, Ufuk"],"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":["Bresler, Yoram"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-10-07T22:49:48Z","date_published":"2020-10-07T22:49:48Z","updated_at":"2026-07-22T22:24:48Z","subjects":["Ultrasound Localization Microscopy","Signal Processing","Velocity Filtering"],"languages":["en"],"rights":["Copyright 2020 Ufuk Soylu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108675","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bresler, Yoram"]},{"key":"dc:creator","label":"Author","values":["Soylu, Ufuk"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-10-07T22:49:48Z","2022-10-07T22:50:13Z","2020-07-08","2020-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"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":["Ultrasound Localization Microscopy","Signal Processing","Velocity Filtering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Ufuk Soylu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108675"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ultrasound Localization Microscopy (ULM) offers a cost-effective modality for microvascular imaging by using intravascular contrast agents (microbubbles). However, ULM has a fundamental trade-off between acquisition time and spatial resolution, which makes clinical translation challenging. In this thesis, in order to circumvent the trade-off, we pose the localization problem as a signal processing problem and introduce a filtering operation that is capable of separating microbubble contrast agents into different subgroups based on their vector velocities while simultaneously offering blood velocity mapping at super resolution, without tracking individual microbubbles. We define the filtering operation in three-dimensional (3D) Fourier domain and provide rigorous theoretical analysis on the performance of the filtering operation. Numerical experiments validate that the proposed filtering method is able to separate the microbubbles with respect to the speed and direction of their motion. In combination with subsequent localization of microbubble centers, e.g. by matched filtering, velocity filter signicantly improves the quality of reconstructed vessel structure map and provides blood flow information. Overall, the proposed imaging pipeline in this thesis, eliminates the need of using diluted microbubble injections to improve image quality, thus helping to circumvent the trade-off between acquisition time and spatial resolution. Conveniently, because the velocity filtering operation can be implemented by fast Fourier transforms (FFTs) it admits fast, and potentially real-time realization. We believe that the proposed filtering method has the potential to pave the way to clinical translation of ULM.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-08-01","The student, Ufuk Soylu, accepted the attached license on 2020-07-07 at 16:01.","The student, Ufuk Soylu, submitted this Thesis for approval on 2020-07-07 at 16:51.","This Thesis was approved for publication on 2020-07-08 at 14:37.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15515 on 2020-10-02 at 15:49:54","Made available in DSpace on 2020-10-07T22:49:48Z (GMT). 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However, ULM has a fundamental trade-off between acquisition time and spatial resolution, which makes clinical translation challenging. In this thesis, in order to circumvent the trade-off, we pose the localization problem as a signal processing problem and introduce a filtering operation that is capable of separating microbubble contrast agents into different subgroups based on their vector velocities while simultaneously offering blood velocity mapping at super resolution, without tracking individual microbubbles. We define the filtering operation in three-dimensional (3D) Fourier domain and provide rigorous theoretical analysis on the performance of the filtering operation. Numerical experiments validate that the proposed filtering method is able to separate the microbubbles with respect to the speed and direction of their motion. In combination with subsequent localization of microbubble centers, e.g. by matched filtering, velocity filter signicantly improves the quality of reconstructed vessel structure map and provides blood flow information. Overall, the proposed imaging pipeline in this thesis, eliminates the need of using diluted microbubble injections to improve image quality, thus helping to circumvent the trade-off between acquisition time and spatial resolution. Conveniently, because the velocity filtering operation can be implemented by fast Fourier transforms (FFTs) it admits fast, and potentially real-time realization. We believe that the proposed filtering method has the potential to pave the way to clinical translation of ULM.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-08-01","The student, Ufuk Soylu, accepted the attached license on 2020-07-07 at 16:01.","The student, Ufuk Soylu, submitted this Thesis for approval on 2020-07-07 at 16:51.","This Thesis was approved for publication on 2020-07-08 at 14:37.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15515 on 2020-10-02 at 15:49:54","Made available in DSpace on 2020-10-07T22:49:48Z (GMT). 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