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  • 1
    Online Resource
    Online Resource
    Wiley ; 2012
    In:  PAMM Vol. 12, No. 1 ( 2012-12), p. 683-684
    In: PAMM, Wiley, Vol. 12, No. 1 ( 2012-12), p. 683-684
    Abstract: Positron‐Emission Tomography (PET) is an imaging technique in nuclear medicine used to image physiological processes. A major obstacle is the need for dynamic image reconstruction from low quality PET‐data, which applies in particular for tracers (radioactive water) with fast decay like H 2 15 O when looking for improved spatial resolution. Here we present a model‐based approach to overcome those difficulties. We derive a set of differential equations able to represent the kinetic behavior of H 2 15 O PET tracers during cardiac perfusion. In this model one takes into account the exchange of materials between artery, tissue and vein, which predicts the tracer activity if the reaction rates, velocities, and diffusion coefficients are known. One then interprets the computation of these distributed parameters (spatially dependent only) as a nonlinear inverse problem, which we solve using variational regularization approaches. For the minimization we use the gradient‐based methods and Forward‐Backward Splitting. The main advantage is the reduction of the degrees of freedom, which makes the problem overdetermined and thus allows to proceed to low quality data. (© 2012 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
    Type of Medium: Online Resource
    ISSN: 1617-7061 , 1617-7061
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2012
    detail.hit.zdb_id: 2078931-2
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  • 2
    Online Resource
    Online Resource
    Walter de Gruyter GmbH ; 2018
    In:  Journal of Inverse and Ill-posed Problems Vol. 26, No. 2 ( 2018-4-1), p. 185-200
    In: Journal of Inverse and Ill-posed Problems, Walter de Gruyter GmbH, Vol. 26, No. 2 ( 2018-4-1), p. 185-200
    Abstract: The aim of this paper is to discuss potential advances in PET kinetic models and direct reconstruction of kinetic parameters. As a prominent example we focus on a typical task in perfusion imaging and derive a system of transport-reaction-diffusion equations, which is able to include macroscopic flow properties in addition to the usual exchange between arteries, veins, and tissues. For this system we propose an inverse problem of estimating all relevant parameters from PET data. We interpret the parameter identification as a nonlinear inverse problem, for which we formulate and analyze variational regularization approaches. For the numerical solution we employ gradient-based methods and appropriate splitting methods, which are used to investigate some test cases.
    Type of Medium: Online Resource
    ISSN: 1569-3945 , 0928-0219
    Language: English
    Publisher: Walter de Gruyter GmbH
    Publication Date: 2018
    detail.hit.zdb_id: 2041913-2
    SSG: 11
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  • 3
    Online Resource
    Online Resource
    The Royal Society ; 2014
    In:  Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Vol. 372, No. 2028 ( 2014-11-13), p. 20130402-
    In: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, The Royal Society, Vol. 372, No. 2028 ( 2014-11-13), p. 20130402-
    Abstract: The identification of production functions from data is an important task in the modelling of economic growth. In this paper, we consider a non-parametric approach to this identification problem in the context of the spatial Solow model which allows for rather general production functions, in particular convex–concave ones that have recently been proposed as reasonable shapes. We formulate the inverse problem and apply Tikhonov regularization. The inverse problem is discretized by finite elements and solved iteratively via a preconditioned gradient descent approach. Numerical results for the reconstruction of the production function are given and analysed at the end of this paper.
    Type of Medium: Online Resource
    ISSN: 1364-503X , 1471-2962
    RVK:
    Language: English
    Publisher: The Royal Society
    Publication Date: 2014
    detail.hit.zdb_id: 208381-4
    detail.hit.zdb_id: 1462626-3
    SSG: 11
    SSG: 5,1
    SSG: 5,21
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