Opendata, web and dolomites


Dementia modelling

Total Cost €


EC-Contrib. €






Project "DEMO" data sheet

The following table provides information about the project.


Organization address
postcode: 2100

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Denmark [DK]
 Project website
 Total cost 853˙451 €
 EC max contribution 853˙451 € (100%)
 Programme 1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
 Code Call H2020-MSCA-ITN-2016
 Funding Scheme MSCA-ITN-EID
 Starting year 2016
 Duration (year-month-day) from 2016-09-01   to  2020-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BIOMEDIQ AS DK (KOBENHAVN) coordinator 580˙163.00
2    UNIVERSITY COLLEGE LONDON UK (LONDON) participant 142˙717.00
3    KING'S COLLEGE LONDON UK (LONDON) participant 130˙570.00


 Project objective

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.


List of deliverables.
Recruitment completed Other 2019-07-24 11:09:15
Webpage completion Websites, patent fillings, videos etc. 2019-07-18 19:26:50

Take a look to the deliverables list in detail:  detailed list of DEMO deliverables.


year authors and title journal last update
List of publications.
2019 Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, M. Jorge Cardoso, Marc Modat, Sébastien Ourselin, Lauge Sørensen
Training recurrent neural networks robust to incomplete data: Application to Alzheimer’s disease progression modeling
published pages: 39-46, ISSN: 1361-8415, DOI: 10.1016/
Medical Image Analysis 53 2019-10-08
2018 Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, M. Jorge Cardoso, Marc Modat, Sebastien Ourselin, Lauge Sørensen
Robust training of recurrent neural networks to handle missing data for disease progression modeling
published pages: , ISSN: 2331-8422, DOI:
1st International Conference on Medical Imaging with Deep Learning (MIDL) 2019-07-18
2018 Mauricio Orbes-Arteaga, Lauge Sørensen, Marc Modat, M. Jorge Cardoso, Sébastien Ourselin, Mads Nielsen, Akshay Pai
Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 MRIs
published pages: , ISSN: 2331-8422, DOI:
1st International conference on Medical Imaging with Deep Learning (MIDL) 2019-07-18

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The information about "DEMO" are provided by the European Opendata Portal: CORDIS opendata.

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