Upcoming Events

Edinburgh Imaging PhD Expo 2018 Oct 18, 2018 01:30 PM - 06:00 PM — Room G07, Informatics Building, University of Edinburgh
PET is Wonderful Annual Meeting 2018 Oct 29, 2018 09:00 AM - 05:00 PM — South Hall Complex, Pollock Halls, University of Edinburgh
8th SINAPSE Neuro-oncology Meeting Oct 30, 2018 09:30 AM - 04:00 PM — Royal College of Physicians and Surgeons of Glasgow, 232-242 St Vincent Street, Glasgow
7th Annual Scottish Radiotherapy Research Forum Nov 01, 2018 10:00 AM - 04:30 PM — Stirling Court Hotel, University of Stirling
Scottish Radiological Society Annual General Meeting 2018 Nov 02, 2018 12:00 AM — President’s Suite, BT Murrayfield Stadium, Edinburgh

People




Professor Matteo Zanda

Research interests in bioorganic/medicinal chemistry with Imaging Technologies, particularly Positron Emission Tomography (PET) with applications in brain imaging and oncology.

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Ms Dongyu Zhang


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Dr Jianguo Zhang


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Miss Qiyue Zhao


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Mr Kanheng Zhou

Optical Coherence Tomography, Optical Coherence Elastography, Shear wave elastography, Surface acoustic wave elastography, High intensity focused ultrasound

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Mr Xiaowei Zhou


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Mr Fan Zhu

Description of PhD:

 

Deconvolution is used in perfusion imaging to obtain the impulse residue function (IRF) that is then used to create parametric maps of relevant haemodynamic quantities such as CBF, CBV and MTT. A popular method to achieve this is Singular Value Decomposition (SVD), but it has been shown that for MRI Gaussian Process Deconvolution (GPD) is comparable to SVD when determining the maximum of the IRF, and superior estimating the full IRF. Furthermore, it clearly outperforms SVD when the signal-to-noise ratio improves.   Gaussian Process regression arises from a Bayesian approach to the regression problem, and as in the case of other kernel-based methods the scalability with data size is very poor. This constitutes the main drawback of this technique to compute deconvolution when compared with SVD.  The currently running Wyeth-TMRC multicenter project on acute stroke brings the opportunity to test this technique with data from several SINAPSE centres and different modalities. This PhD project will benefit from the expertise in these centres and would seek to collaborate with them through the centres’ contacts: M.J. McLeod (Aberdeen), J. Wardlaw (Edinburgh) and K. Muir (Glasgow).  The project will research the possibilities that distributed (and parallel) computing brings to make this method usable in practice. As a by product, the project will produce a data processing framework prototype reusable for other types of image processing.

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Mr John Zurowski


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Mr wael ageeli


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Miss wajiha bano


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