3rd International Conference on Medical Imaging with Deep Learning Jul 06, 2020 - Jul 08, 2020 — Virtual Meeting (online)
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 25, 2020 - Aug 28, 2020 — KCL Waterloo Campus, London
Scottish Dementia Research Consortium Annual Conference 2020 [rescheduled] Sep 07, 2020 10:00 AM - 04:00 PM — Radisson Blu, 301 Argyle St, Glasgow

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: 'MRI hardware' returned 9 Result(s)

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Dr Michael Bradnam

Oncology imaging, including imaging of paediatric neuroendocrine tumours

Radiotherapy using unsealed sources of radiation

SPECT technology and image reconstruction

MR technology

Electrophysiology equipment

Visual development in preterm, newborn and infants

Objective assessment of visual acuity

Signal detection

Modelling visual impairment

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Sean Denham


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Dr John Foster


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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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Dr James Ross


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Shaun R. Stone

Shaun Stone is a final year Ph.D. ERC studying Medical Imaging at the University of Aberdeen under the supervision of Professor Alison Murray. He is the deputy student lead of the Image Analysis group of the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE), a consortium of seven Scottish universities. His research is titled “Cognitive Reserve Estimation Models from Brain MRI in Healthy Ageing: A Machine Learning Approach”, under the supervision of Professor Alison D. Murray (University of Aberdeen), Dr Roger Staff (NHS), Professor Joanna Wardlaw, Professor Craig Ritchie (University of Edinburgh) and Dr Robin Wolz (IXICO). Cosupervisors to this project at Dr Gordon Waiter and Dr Anca Sandu-Giuraniuc. His project is funded by SINAPSE and industry partners IXICO.

His project aims to identify the most important MR imaging biomarkers that influence differences in cognitive resilience. That is, given the life-course of an individual, what are the imaging characteristics that allow us to predict increased risk of cognitive impairment? Further, what factors provide resilience against age- and disease-related brain changes? He is passionate about computational neuroscience, artificial intelligence and computer-assisted diagnosis in medical imaging. Shaun completed his undergraduate (BSc) degree in Psychology with Neuroscience, and postgraduate (MSc) degree in Neuroimaging at Bangor University, North Wales - where he gained experience using a range of neuroimaging techniques. Shaun continues to learn, using his neuro-background to transfer into computational medicine and diagnostic imaging and is looking forward to his future career in research or industry, thanks to this opportunity.

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Miss Charlotte Sutherland


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Dr Sydney Williams


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Mr Steven Winata


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