PET is Wonderful Annual Meeting 2021 Oct 26, 2021 12:00 AM — Virtual Meeting (online)
NRS Mental Health Network Annual Scientific Meeting 2021 Nov 02, 2021 09:00 AM - 05:00 PM — Royal College of Physicians, Edinburgh (and online)

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

People

Your search for Keyword: 'Dementia' returned 26 Result(s)

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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 Elastography Episodic memory Evidence Based Radiology Executive Function Fetal and Child development Field-cycling Functional Connectivity Functional MRI (fMRI) Image analysis Image processing Image segmentation Image-guided intervention 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 Radiotherapy 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

Dr Lucia Ballerini

I am a researcher in image analysis. I developed theoretical and application oriented methods. I have been working with different kind of images: medical, food, radar, robotic and forensic images. Recently I worked with skin lesion images and retinal images. See my 100+ publications (google scholar or researchgate) for more details

I am presently working MR brain images.

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Mr Thomas Biggans


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Dr Una Clancy

I am analysing subtle symptoms of cerebral SVD in in relation to imaging correlates, which is important in order to translate radiological evidence of ‘silent’ SVD into clinically significant outcomes. I am characterising these symptoms in relation to progression of SVD radiologically based on longitudinal disease progression on MRI. This work will allow us to identify those individuals with early features of SVD, before significant disease progression occurs. Identifying the disease early will be central to future dementia and stroke prevention. I am currently involved in the Mild Stroke Study 3, the R4VaD Study and the LACI-2 Study.

Supervisors: Prof. Joanna Wardlaw and Dr Fergus Doubal

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Dr Simon R. Cox


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Dr Amir Dehsarvi

Classification, Cartesian Genetic Programming, Evolutionary Algorithms, Machine Learning, MRI/fMRI data analysis, Mediation Analysis, and Neurodegenerative Diseases Diagnosis (Biomarkers) and Monitoring.

 

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Sean Denham


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Dr David Alexander Dickie

Structural brain ageing

White matter disease

Cognitive ageing

Stroke

Image Analysis

Alzheimer's disease and other dementias

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Miss Emma Elliott


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Dr Javier Escudero

In my research, I create and apply data analysis tools to extract information from biomedical signals and clinical time series.

 

My main aim is to reveal the subtle changes that major diseases (e.g., Alzheimer's and epilepsy) cause in the brain activity.

 

In collaboration with researchers at Edinburgh, across the UK and overseas, I am currently working in the processing and analysis of biomedical signals, particularly human brain activity. By developing and applying signal processing methods, I aim at increasing our understanding of how several brain conditions progress. Of particular interest is the evaluation of brain functional connectivity in both neurodevelopmental and neurodegenerative diseases to understand how they affect the way in which different brain regions interact with each other. I am also interested in the interplay between structure and function in the brain and in the application of pattern recognition techniques to highly-dimensional clinical datasets to support decision making. Finally, I also work in the development of non-invasive methods for rehabilitation purposes, being either the dexterous controls prostheses for amputees or brain-computer interfaces.

 

For additional information, please see: http://www.research.ed.ac.uk/portal/jescuder

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Miss Charlene Hamid


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