Medical Image Understanding and Analysis Conference 2020 Jul 15, 2020 - Jul 17, 2020 — Virtual Meeting (online)
CAFACHEM 2020 Summer School on Organic & Halogen Radiochemistry Aug 26, 2020 - Aug 28, 2020 — Virtual Meeting (online)
Scottish Dementia Research Consortium Annual Conference 2020 [rescheduled] Sep 07, 2020 10:00 AM - 04:00 PM — Radisson Blu, 301 Argyle St, Glasgow
Society for Magnetic Resonance Angiography - SMRA2020 VIRTUAL Sep 11, 2020 - Sep 13, 2020 — Virtual Meeting (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: 'Statistics' returned 20 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 Cognitive Control 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 Ultrasound White matter disease

Miss Muzammal Ayesha


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Dr Viveka Biswas

Stroke medicine, Neurology, Neuroradiology

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Miss Subarnarekha Chatterji


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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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Mrs Jyothsna Divyananda


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Dr Robin Ince


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Mr Conor MacDonald

PhD student in clinical imaging and data mining. Focus on predictive markers of vascular access outcome for haemodialysis.

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Ms Shadia Mikhael


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Dr. Carlos Mugruza-Vassallo

Description of PhD:

Fox et al. (Fox et al., 2005)  hypothesize that a dorsal ‘goal-driven’ attention network controls environmentally directed processes (perception and action) and a ‘default network’ controls internally directed processes (memory and introspection). Within this model it was hypothesised that a ventral ‘stimulus-driven’ network facilitates reorientation in goal driven attention as well as between internally and externally directed processing modes. We have demonstrated abnormal patterns of brain activity in both the goal-driven and stimulus driven networks in individuals with a history of mild concussion (Potter et al., 2001) and in patients diagnosed with schizophrenia (Potter et al., 2008). These abnormalities may result from reduced effectiveness of frontal control caused by diffuse neurotransmitter imbalances (Rolls et al., 2008). The research extended our previous work by providing a better understanding of the role of the stimulus-driven system in switching between goal-driven and default processing modes (Mugruza-Vassallo, 2015 http://discovery.dundee.ac.uk/portal/files/8267183/CAR_FE_PhD2015_VIVA.pdf ).

 

Cognitive Computing and Neuroscience Group at UNTELS

Members:

Carlos Andrés Mugruza Vassallo -

Itamar Franco Salazar Reque - M.Sc. Evaluación de técnicas del problema inverso para estudio del número de señales de electroencefalograma para mecanismos cognitivos. Postgrado en Procesamiento Digital de Señales. Universidad Nacional de Ingeniería.

Yamina Andrade Huaman - “Estudio del tiempo de reacción ante un evento simulado de sismo en una adaptación de videojuego 2d para la UNTELS”. Programa de Graduación de la EAP Ing. Electrónica y Telecomunicaciones-UNTELS

Fredrich Huamani Atao - ““Diseño, implementación y evaluación de un experimento visual 2d en computación cognitiva en la UNTELS”. Programa de Graduación de la EAP Ing. Electrónica y Telecomunicaciones-UNTELS

Melina Machaca Saavedra

Daniel Cóndor

Carlos Mamani

Carlos Escobar Ulloa -

Donny Hanco -

Luz Elena Collado Arapa -

Edward Ventura Barrientos

 

Collaboration and Aims: Carlos Mugruza is working between Computing and Cognitive Neuroscience. In the last years he has worked with EEG and fMRI, his experiments are between oddball paradigms, Go-NoGo, 3D and augmented reality.

Since 2013, Carlos Mugruza and Douglas Potter continued the analysis of data between the University of Dundee and the Cognitive Neuroscience Group in Peru. Therefore the aims are:

- To better characterise the function of the stimulus-driven system by determining the effects of task load and distractor contingency on  the temporal relationships between the components of the stimulus-driven system.

- To better characterise the function of the stimulus-driven system by inducing more explicit switching and maintenance of processing modes.

 

Experimental Methods: Combine fMRI and EEG to visualise selective activation or suppression of posterior and anterior components of the ‘stimulus-driven’ control system while participants perform a number decision paradigm in which the temporal and spatial relationship of goal relevant and distractor stimuli are systematically manipulated. Basically EEG signals are modeled as

EEG = β0 + ∑ βiSi + β3A3 + Error

This equation considers 2 categorical variables as regressors.

 

Theoretical Methods: An information theory framework is being used. Simulation of the information of the auditory parity experiment has shown around 300 ms CTOA a saddle indentation in the curve of the information measure based on the states of the incoming signal.


Expected Outcomes: The development of optimised, inexpensive (EEG), measures of cognitive control for use assessment attention functions. Specific use are in:

- human computation in disaster and resilience

- cogntive strategies in anaemia

- neuromarketing and

- pharmacological efficacy in patients diagnosed with schizophrenia, depression and mild cognitive impairment.

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Miss Emma Pead

Assessing neurodegeneration of the retina and brain with ultra-widefield retinal images.

Philosophers have often described the eye as the window to the soul. This can also be addressed on the scientific basis that the retina is a direct window into the health of the brain (or CNS). My focus is on the development of automatic detection algorithms of biomarkers for Age-related macular degeneration (AMD) and Alzheimer’s disease (AD) in retinal images. AMD is often characterised by the presence of drusen, small deposits of cellular debris, in retinal images appearing as bright white/yellow spots. The hallmark of AD is the presence of Aβ-amyloid which has also been shown to be present in drusen. There are currently no treatments for late AMD, therefore early diagnosis and detection of drusen could provide timely treatment. Additionally, the potential of drusen as an early biomarker of AD will be explored. My methods focus on image analysis and quantification of fundus and OptoMap images (Optos) and application of machine learning algorithms as an automatic detection strategy.

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