Source localization of reaction-diffusion models for brain tumors

Rym Jaroudi*, George Baravdish, Freddie Åström, B. Tomas Johansson

*Corresponding author for this work

    Research output: Chapter in Book/Published conference outputConference publication


    We propose a mathematically well-founded approach for locating the source (initial state) of density functions evolved within a nonlinear reaction-diffusion model. The reconstruction of the initial source is an ill-posed inverse problem since the solution is highly unstable with respect to measurement noise. To address this instability problem, we introduce a regularization procedure based on the nonlinear Landweber method for the stable determination of the source location. This amounts to solving a sequence of well-posed forward reaction-diffusion problems. The developed framework is general, and as a special instance we consider the problem of source localization of brain tumors. We show numerically that the source of the initial densities of tumor cells are reconstructed well on both imaging data consisting of simple and complex geometric structures.

    Original languageEnglish
    Title of host publicationPattern recognition
    Subtitle of host publication38th German Conference, GCPR 2016, Hannover, Germany, September 12-15, 2016, Proceedings
    EditorsBodo Rosenhahn, Bjoern Andres
    Place of PublicationCham (CH)
    Number of pages12
    ISBN (Electronic)978-3-319-45886-1
    ISBN (Print)978-3-319-45885-4
    Publication statusPublished - 27 Aug 2016
    Event38th German Conference on Pattern Recognition - Hannover, Germany
    Duration: 12 Sept 201615 Sept 2016

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference38th German Conference on Pattern Recognition
    Abbreviated titleGCPR 2016


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