Print Email Facebook Twitter Improving Ultrafast Doppler Imaging using Subspace Tracking Title Improving Ultrafast Doppler Imaging using Subspace Tracking Author Generowicz, Bas (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Leus, Geert (mentor) Degree granting institution Delft University of Technology Programme Electrical Engineering | Signals and Systems Date 2019-01-24 Abstract High frame rate Doppler ultrasound imaging provides a new way to image blood motion at thousands of frames per second. It has gained popularity due to its high spatio-temporal resolution, which is re- quired to distinguish blood motion from clutter signals caused by slow moving tissue. Since the flow of blood inside the brain is coupled to neural activity it is now possible to study brain function with the use of Ultrafast Doppler. This technique is called functional UltraSound (fUS), and forms a new and exciting research area. fUS relies heavily on optimized signal processing techniques to acquire and process a large amount of high frame-rate images in real-time. This thesis is about establishing the software backbone to allow for fUS experiments. Furthermore, it describes the development and implementation of a computationally efficient method of obtaining vascular images, based on the Projection Approximation Subspace Tracking (PAST) method. The PAST algorithm is able to display accurate representations of the blood subspace, while maintaining a lower computational complexity than the state-of-the-art method, making it suitable for Doppler imaging. When applied to fUS, the ex- ponentially weighted PASTd method achieves a similar performance in highlighting the functional areas of the brain as compared to the current state-of-the-art method, over multiple functional experiments, however with the benefit of lower computational complexity. These findings highlight the potential of applying PAST methods to Ultra- fast Doppler imaging. Subject DopplerUltrasoundfunctional ultrasoundSVDSubspace Tracking To reference this document use: http://resolver.tudelft.nl/uuid:51cfae12-461d-4910-bd8f-a0dff5237af8 Part of collection Student theses Document type master thesis Rights © 2019 Bas Generowicz Files PDF Bas_Generowicz_Thesis.pdf 18.09 MB Close viewer /islandora/object/uuid:51cfae12-461d-4910-bd8f-a0dff5237af8/datastream/OBJ/view