project . 2016 - 2021 . On going

LEASP

Learning spatiotemporal patterns in longitudinal image data sets of the aging brain
Open Access mandate for Publications European Commission
  • Funder: European CommissionProject code: 678304 Call for proposal: ERC-2015-STG
  • Funded under: H2020 | ERC | ERC-STG Overall Budget: 1,499,890 EURFunder Contribution: 1,499,890 EUR
  • Status: On going
  • Start Date
    01 Sep 2016
    End Date
    31 Aug 2021
  • Detailed project information (CORDIS)
  • Open Access mandate
    Research Data: No
Description
Time-series of multimodal medical images offer a unique opportunity to track anatomical and functional alterations of the brain in aging individuals. A collection of such time series for several individuals forms a longitudinal data set, each data being a rich iconic-geometric representation of the brain anatomy and function. These data are already extraordinary complex and variable across individuals. Taking the temporal component into account further adds difficulty, in that each individual follows a different trajectory of changes, and at a different pace. Furthermore, a disease is here a progressive departure from an otherwise normal scenario of aging, so th...
Partners
Description
Time-series of multimodal medical images offer a unique opportunity to track anatomical and functional alterations of the brain in aging individuals. A collection of such time series for several individuals forms a longitudinal data set, each data being a rich iconic-geometric representation of the brain anatomy and function. These data are already extraordinary complex and variable across individuals. Taking the temporal component into account further adds difficulty, in that each individual follows a different trajectory of changes, and at a different pace. Furthermore, a disease is here a progressive departure from an otherwise normal scenario of aging, so th...
Partners
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