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    FEMONUM: A Framework for Whole Body Pregnant Woman Modeling from Ante-Natal Imaging Data

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    Date
    2011
    Author
    Alcalde, Juan Pablo de la Plata
    Anquez, Jérémie
    Bibin, Lazar
    Boubekeur, Tamy ORCID
    Angelini, Elsa
    Bloch, Isabelle
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    Abstract
    Anatomical models of pregnant women can be used in several applications such as numerical dosimetry to assess the potential effects of electromagnetic fields on biological tissues, or medical simulations for delivery planning. Recent advances in medical imaging have enabled the generation of realistic and detailed models of human beings. This paper describes FEMONUM, a complete methodological framework for the construction of pregnant woman models based on medical images and their segmentation. FEMONUM combines several computer graphics methods, such as surface reconstruction and physics-based computer animation to model and deform pregnant women abdomens, to simulate different fetal positions and sizes and also different morphologies of the mother, represented with a synthetic woman body envelope. A set of 16 models, anatomically validated by clinical experts, is presented and is made available online to the scientific community. These models include detailed information on the utero-fetal units and cover different gestational stages with various fetal positions.
    BibTeX
    @inproceedings {10.2312:EG2011:med:017-020,
    booktitle = {Eurographics 2011 - Dirk Bartz Prize},
    editor = {K. Buehler and A. Vilanova},
    title = {{FEMONUM: A Framework for Whole Body Pregnant Woman Modeling from Ante-Natal Imaging Data}},
    author = {Alcalde, Juan Pablo de la Plata and Anquez, Jérémie and Bibin, Lazar and Boubekeur, Tamy and Angelini, Elsa and Bloch, Isabelle},
    year = {2011},
    publisher = {The Eurographics Association},
    ISSN = {1017-4656},
    DOI = {10.2312/EG2011/med/017-020}
    }
    URI
    http://dx.doi.org/10.2312/EG2011/med/017-020
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA