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    Automatic 3D model-based method for liver segmentation in MRI based on Active Contours and Total Variation minimization

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    Automatic 3D model-based ... (339.4Kb)
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    URI: http://hdl.handle.net/11556/243
    ISSN: 1746-8094
    DOI: 10.1016/j.bspc.2015.04.005
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    Author/s
    Bereciartua, Arantza; Picon, Artzai; Galdran, Adrian; Iriondo, Pedro M.
    Date
    2015-07
    Keywords
    computer vision
    Image segmentation
    magnetic resonance imaging
    variational techniques
    active contours
    3D
    model-based
    Abstract
    Liver cancer is one of the leading causes of cancer-related mortality worldwide. Non-invasive techniques of medical imaging such as Computerized Tomography (CT) and Magnetic Resonance Imaging (MRI) are often used by radiologists for diagnosis and surgery planning. With the aim of assuring the most reliable intervention planning to surgeons, new accurate methods and tools must be provided to locate and segment the regions of interest. Automated liver segmentation is a challenging problem for which promising results have been achieved mostly for CT. However, MRI is required by radiologists, since it offers better information for diagnosis purposes. MRI liver segmentation represents a challenge due to the presence of characteristic artifacts, such as partial volumes, noise, low contrast and poorly defined edges of the liver in relation to adjacent organs. In this paper, we present a method for MRI automatic 3D liver segmentation by means of an Active Contour model extended to 3D and minimized ...
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