Medical Imaging Convention [rescheduled] Mar 09, 2021 - Mar 10, 2021 — National Exhibition Centre, Birmingham, England
9th SINAPSE Neuro-oncology Imaging Meeting [rescheduled] Mar 11, 2021 09:30 AM - 03:30 PM — West Park Conferencing & Events, 319 Perth Road, Dundee DD2 1NN
Total Body PET 2020 conference [rescheduled] Jun 05, 2021 - Jun 07, 2021 — McEwan Hall, University of Edinburgh

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

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ADHD Addictions Ageing Alzheimer's Anaesthesia Artificial Intelligence Attention Autism Bioorganic chemistry Bipolar disorder Brain temperature CT Cardiac imaging Cardiovascular Imaging Carotid Doppler ultrasound Cerebral atrophy Chemistry Clinical decision support Cognitive Control Computer vision DTI-tractography Data protection Database Deep Learning Dementia Depression Diffusion imaging Disorders of Consciousness Doppler ultrasound EEG ERP Episodic memory Evidence Based Radiology Executive Function Fetal and Child development Field-cycling Free radicals Functional Connectivity Functional MRI (fMRI) Image analysis Image processing Image segmentation Imaging biomarkers Imitation Impaired Consciousness Kinetic Modelling Lacunar stroke Language Large animal imaging Leukoaraiosis Lung Imaging MRA MRI hardware MRI pulse sequences MRS Machine Learning Magnetization transfer Medical visualization Memory Meta-analysis Microvascular MRI Molecular Imaging Multicentre studies Muscle Imaging and Measurement NMR relaxometry Neurodevelopment Neuroinformatics Neurology Neuroradiology Novel Radiotracers Novel imaging methods Nuclear Medicine Oncologic Imaging Oncology Optical imaging PET Parallel computing Perfusion imaging (CT and MR) Permeability imaging (MR) Physics Preclinical Imaging Predictive Classification Psychiatry Radiochemistry Radiology Radiomics Retinal imaging SPECT Schizophrenia Semantic Memory Simulation Small vessel disease Statistics Stroke Structural imaging TBI Texture analysis Thrombolysis Time series analyses Translational Imaging Ultra-high field MRI Ultrasound White matter disease

Ms Dongyu Zhang


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Dr Jianguo Zhang


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Miss Qiyue Zhao


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Mr Xiaowei Zhou


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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 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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Miss Xingxing Zhu


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Dr Polina Zioga


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Mr John Zurowski


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Miss wajiha bano


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