DEBRA

Detection of Brain Abnormality

 Coordinatore UNIVERSITY OF PATRAS 

 Organization address address: UNIVERSITY CAMPUS RIO PATRAS
city: RIO PATRAS
postcode: 26500

contact info
Titolo: Prof.
Nome: Anastasios
Cognome: Bezerianos
Email: send email
Telefono: 302611000000
Fax: 302611000000

 Nazionalità Coordinatore Greece [EL]
 Totale costo 75˙000 €
 EC contributo 75˙000 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-IRG-2008
 Funding Scheme MC-IRG
 Anno di inizio 2009
 Periodo (anno-mese-giorno) 2009-04-01   -   2012-03-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    UNIVERSITY OF PATRAS

 Organization address address: UNIVERSITY CAMPUS RIO PATRAS
city: RIO PATRAS
postcode: 26500

contact info
Titolo: Prof.
Nome: Anastasios
Cognome: Bezerianos
Email: send email
Telefono: 302611000000
Fax: 302611000000

EL (RIO PATRAS) coordinator 75˙000.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

alzheimer    brain    neuroimaging    detection    expert    progression    interpretation    measuring    disease    treatments    time    conventional    diabetic    lesions    imaging    suitable    human    cerebrovascular    mri    abnormality    cvd    reproducible    longitudinal    segmentation   

 Obiettivo del progetto (Objective)

'Cerebrovascular disease (CVD) is a very significant health problem, especially in view of the increasing aging population. It is highly prevalent in diabetic populations and is also a major cause of dementia, individually or as an additive factor to other pathologies, such as Alzheimer’s. Therefore measuring disease burden, progression, and response to treatments is very important for patient management. MRI is currently the most widely used way to characterize in vivo the type and extent of brain lesions in CVD and has been used in several large neuroimaging studies. However, characterization of CVD has largely relied on qualitative, subjective, and not easily reproducible methods of human expert-based interpretation. Computer-based methods for measuring CVD offer great potential, since they are quantitative; reproducible, and particularly suitable for longitudinal studies monitoring disease progression and response to candidate treatments. Most methods have focused on the segmentation of Multiple Sclerosis lesions, whereas less attention has been given to brain lesion segmentation in elderly individuals and Alzheimer’s disease or diabetic patients. The project DeBrA (Detection of Brain Abnormality) includes the development and implementation of medical imaging techniques for measuring CVD and its change over time, from multi-parametric MR images by employing advanced 4-dimensional (space X time) segmentation methods based on pattern classification and statistical modeling. The goal is to determine whether the new methodology will provide more stable measurements of longitudinal change in CVD, compared to relatively more conventional methods and therefore increase the sensitivity of detecting subtle effects. Moreover, while the tools will be initially developed for measuring CVD, they will be made suitable to hold widespread potential for applications in other neuroimaging studies involving abnormality detection.'

Introduzione (Teaser)

Magnetic resonance imaging (MRI) has been the tool of choice in diagnosis of brain lesions related to abnormal blood supply (cerebrovascular disease, or CVD). An EU-funded project is seeking to improve conventional MRI-based methods of CVD detection such that they are less dependent on human expert-based interpretation.

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