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Dementia modelling


Dementia constitutes a major burden on society, both in monetary costs and the suffering of patients and their relatives. It comprises a number of diseases including Alzheimer’s disease (AD) and vascular dementia (VaD). In recent years, imaging biomarkers have been developed including measures of brain morphology (MRI T1), vascular pathologies (MRI T2*/FLAIR), white matter abnormalities (MRI DWI), perfusion (MRI ASL), glucose turnover (PET FDG), and accumulation of pathological proteins (PET PIB/AV45). Quantitative measures using these biomarkers in large cohort studies have the potential to model the pathological process of the disease. This proposal would create an innovative training network, in which early stage researchers will develop new computational imaging biomarkers, under the supervision of experienced researchers, for the purpose of modeling dementia etiology. One researcher will investigate quantification of vascular pathologies, another will develop quantitative measures of white matter abnormalities from structural MRI, and the final researcher will construct a quantitative model of disease etiology using a maximum-likelihood framework. The early stage researchers will be enrolled as PhD students at University College London (UCL) under the EPSRC Centre for Doctoral Training in Medical Imaging (CDT), which is based in Centre for Medical Image Computing (CMIC), with the Dementia Research Centre (DRC) being one of the main clinical collaborators for CDT studentships. However, they will spend the majority of time at the research facilities of Biomediq A/S, Copenhagen Denmark, where they will be exposed to industry and work under professional guidance.

Field of science

  • /medical and health sciences/basic medicine/pathology
  • /agricultural sciences/animal and dairy science/pets
  • /medical and health sciences/basic medicine/neurology/alzheimer
  • /engineering and technology/medical engineering/diagnostic imaging
  • /natural sciences/computer and information sciences/artificial intelligence/computational intelligence
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning/deep learning

Call for proposal

See other projects for this call

Funding Scheme

MSCA-ITN-EID - European Industrial Doctorates


Fruebjergvej 3
2100 Kobenhavn
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EU contribution
€ 580 163,76

Participants (2)


Participation ended

United Kingdom
EU contribution
€ 142 717
Gower Street
WC1E 6BT London
Activity type
Higher or Secondary Education Establishments
United Kingdom
EU contribution
€ 130 570,88
WC2R 2LS London
Activity type
Higher or Secondary Education Establishments