Photoacoustic microscopy (PAM), a hybrid modality that combines optical excitation and ultrasonic detection, has attracted considerable attention in basic and translational research. PAM not only enables in vivo label-free vascular imaging at the microscopic level, but also facilitates the assessment of hemodynamics and oxygen metabolism. However, challenges related to image contrast, spatial resolution, and functional analysis hinder its broad applications in biomedicine. This dissertation presents innovative computational techniques to address these challenges. Specially, a sparse coding-based technique is developed to enhance image contrast and ensure robust functional measurements in noisy low-fluence conditions. Additionally, a spatiotemporal red blood cell tracking algorithm, together with a high-speed PAM system, is developed to mitigate resolution anisotropy, providing super-resolved structural and functional images of the 3D microvasculature. Furthermore, a new analytical approach is developed to improve blood flow quantification, achieving high accuracy and computational efficiency. These computational advancements, demonstrated through in vivo applications, hold great potential to leverage the role of PAM in microvascular research.
","abstract_html":"<p>Photoacoustic microscopy (PAM), a hybrid modality that combines optical excitation and ultrasonic detection, has attracted considerable attention in basic and translational research. PAM not only enables in vivo label-free vascular imaging at the microscopic level, but also facilitates the assessment of hemodynamics and oxygen metabolism. However, challenges related to image contrast, spatial resolution, and functional analysis hinder its broad applications in biomedicine. This dissertation presents innovative computational techniques to address these challenges. Specially, a sparse coding-based technique is developed to enhance image contrast and ensure robust functional measurements in noisy low-fluence conditions. Additionally, a spatiotemporal red blood cell tracking algorithm, together with a high-speed PAM system, is developed to mitigate resolution anisotropy, providing super-resolved structural and functional images of the 3D microvasculature. Furthermore, a new analytical approach is developed to improve blood flow quantification, achieving high accuracy and computational efficiency. These computational advancements, demonstrated through in vivo applications, hold great potential to leverage the role of PAM in microvascular research.</p>","abstract_has_math":false,"creators":["Wang, Zhuoying"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Biomedical Engineering","degree_department":null,"school":null,"contributors":["Song Hu","Adam Bauer; Chao Zhou; Joseph O’Sullivan; Quing Zhu"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-12-20T08:00:00Z","date_published":"2024-12-20T08:00:00Z","updated_at":"2026-07-24T06:13:40Z","subjects":["Computational techniques;Functional photoacoustic imaging;Image processing;Photoacoustic microscopy","Engineering"],"languages":["English (en)"],"rights":["I have not registered my thesis with the U.S. Copyright Office, but intend to later."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openscholarship.wustl.edu/eng_etds/1132"],"render_values":[{"text":"https://openscholarship.wustl.edu/eng_etds/1132","href":"https://openscholarship.wustl.edu/eng_etds/1132","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.7936/0geh-1q72","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Song Hu","Adam Bauer; Chao Zhou; Joseph O’Sullivan; Quing Zhu"]},{"key":"dc:creator","label":"Author","values":["Wang, Zhuoying"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2026-12-19T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biomedical Engineering","McKelvey School of Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computational techniques;Functional photoacoustic imaging;Image processing;Photoacoustic microscopy","Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English (en)"]},{"key":"dc:rights","label":"Dc Rights","values":["I have not registered my thesis with the U.S. Copyright Office, but intend to later."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.7936/0geh-1q72","https://openscholarship.wustl.edu/eng_etds/1132"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Photoacoustic microscopy (PAM), a hybrid modality that combines optical excitation and ultrasonic detection, has attracted considerable attention in basic and translational research. PAM not only enables in vivo label-free vascular imaging at the microscopic level, but also facilitates the assessment of hemodynamics and oxygen metabolism. However, challenges related to image contrast, spatial resolution, and functional analysis hinder its broad applications in biomedicine. This dissertation presents innovative computational techniques to address these challenges. Specially, a sparse coding-based technique is developed to enhance image contrast and ensure robust functional measurements in noisy low-fluence conditions. Additionally, a spatiotemporal red blood cell tracking algorithm, together with a high-speed PAM system, is developed to mitigate resolution anisotropy, providing super-resolved structural and functional images of the 3D microvasculature. Furthermore, a new analytical approach is developed to improve blood flow quantification, achieving high accuracy and computational efficiency. These computational advancements, demonstrated through in vivo applications, hold great potential to leverage the role of PAM in microvascular research.
"]},{"key":"dc:title","label":"Title","values":["Computational Techniques for Advancing Photoacoustic Microscopy"]}]}],"canonical_facts":{"dc:contributor":["Song Hu","Adam Bauer; Chao Zhou; Joseph O’Sullivan; Quing Zhu"],"dc:creator":["Wang, Zhuoying"],"dc:date.available":["2026-12-19T08:00:00Z"],"dc:description.abstract":["Photoacoustic microscopy (PAM), a hybrid modality that combines optical excitation and ultrasonic detection, has attracted considerable attention in basic and translational research. PAM not only enables in vivo label-free vascular imaging at the microscopic level, but also facilitates the assessment of hemodynamics and oxygen metabolism. However, challenges related to image contrast, spatial resolution, and functional analysis hinder its broad applications in biomedicine. This dissertation presents innovative computational techniques to address these challenges. Specially, a sparse coding-based technique is developed to enhance image contrast and ensure robust functional measurements in noisy low-fluence conditions. Additionally, a spatiotemporal red blood cell tracking algorithm, together with a high-speed PAM system, is developed to mitigate resolution anisotropy, providing super-resolved structural and functional images of the 3D microvasculature. Furthermore, a new analytical approach is developed to improve blood flow quantification, achieving high accuracy and computational efficiency. These computational advancements, demonstrated through in vivo applications, hold great potential to leverage the role of PAM in microvascular research.
"],"dc:identifier":["https://doi.org/10.7936/0geh-1q72","https://openscholarship.wustl.edu/eng_etds/1132"],"dc:language":["English (en)"],"dc:rights":["I have not registered my thesis with the U.S. Copyright Office, but intend to later."],"dc:subject":["Computational techniques;Functional photoacoustic imaging;Image processing;Photoacoustic microscopy","Engineering"],"dc:title":["Computational Techniques for Advancing Photoacoustic Microscopy"],"thesis:degree_discipline":["Biomedical Engineering","McKelvey School of Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T06:13:40Z"}