Innovative variational methods and gradient flows for 4D biomedical imaging

    Activity: Talk or presentationOral presentation


    In biomedical imaging efficient and accurate reconstruction and tracking methods play a key role. Particularly in cell biology and medical tomography innovative spatio-temporal imaging models using advanced regularization techniques are of strongly growing interest.

    The main goal of this talk is to highlight novel nonlinear PDE constrained variational methods and efficient primal-dual convex optimization methods for joint reconstruction and flow quantification. In those 4D imaging inverse problems, Bregman distances, nonlinear and higher-order regularization and optimal transport are the key ingredients. At the end I will also present a novel achievement for computing the spectral response (ground states) of nonlinear eigenvalue problems in the context of Mumford-Shah type functional with the purpose of automatic multi-scale segmentation.
    Applications will include 4D in-vivo tracking of cells migrating through blood vessels and automatic tumor cell quantification for a EU project called Cancer-ID.
    Period14 Oct 2015
    Held atCentre for Analysis, Scientific computing and Applications (CASA), Netherlands
    Degree of RecognitionNational