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dc.contributor.advisorSboros, Doctor Vassilis
dc.contributor.advisorMcDougall, Professor Steven
dc.contributor.authorVoulgaridou, Vasiliki
dc.date.accessioned2023-02-21T12:01:19Z
dc.date.available2023-02-21T12:01:19Z
dc.date.issued2021-11
dc.identifier.urihttp://hdl.handle.net/10399/4611
dc.description.abstractContrast Enhanced Ultrasound imaging is a safe, reliable, and inexpensive diagnostic method that can provide information on the vascularisation of an organ and is currently applied in a range of diagnostic protocols. This thesis combines the fields of mathematical biology for vascular network modelling with Contrast Enhanced Ultrasound and with Super Resolution Ultrasound to expand the range of diagnostic applications in different conditions. The fact that microbubbles are intravascular agents allows the study of diseases that affect organ vascularisation like obstructions and tumours. Under this scope, vessel networks with certain blood flow conditions and dedicated, large scale organ vascularisation models were constructed, with and without the aforementioned pathologies, and their impact on organ perfusion was studied. Then, Contrast Enhanced Ultrasound imaging was applied on microbubble flow through these vascular networks and the results were compared to the readily available ground truth results. The novelty of this approach lies on combination of the two fields: the mathematical biology models allowed the systematic comparison of healthy organs and of disease on ground truth level, thus allowing the investigation of ultrasound parameters that can be improve image quality or be used as diagnostic markers. The results showed that the use of SRU provides useful information on the structure (recovery of vessel radius) and rheological properties of microcirculation which can be used for early detection of disease.en
dc.language.isoenen
dc.publisherHeriot-Watt Universityen
dc.publisherEngineering and Physical Sciencesen
dc.titleVascular flow modelling for the development of ultrasound contrast imagingen
dc.typeThesisen


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