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  • Adaptive Fuzzy Segmentation of 3D MR Brain Images

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    Author(s)
    Liew, AWC
    Yan, H
    Griffith University Author(s)
    Liew, Alan Wee-Chung
    Year published
    2003
    Metadata
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    Abstract
    A fuzzy c-means based adaptive clustering algorithm is proposed for the furzy segmentation of 3D MR brain images, which are typically corrupted by noise and intensity non-uniformity (INU) artifact. The proposed algorithm enforces the spatial continuity constraint to account for the spatial correlations between image voxels, resulting in the suppression of noise and classification ambiguity. The INU artifact is compensated for by the introduction of a pseudo-3D bias field, which is modeled as a stack of smooth B-spline surfaces with continuity enforced across slices. The efficacy of the proposed algorithm is ...
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    A fuzzy c-means based adaptive clustering algorithm is proposed for the furzy segmentation of 3D MR brain images, which are typically corrupted by noise and intensity non-uniformity (INU) artifact. The proposed algorithm enforces the spatial continuity constraint to account for the spatial correlations between image voxels, resulting in the suppression of noise and classification ambiguity. The INU artifact is compensated for by the introduction of a pseudo-3D bias field, which is modeled as a stack of smooth B-spline surfaces with continuity enforced across slices. The efficacy of the proposed algorithm is demonstrated experimentally using both simulated and real MR images.
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    Conference Title
    PROCEEDINGS OF THE 12TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1 AND 2
    Volume
    2
    Publisher URI
    http://ieeexplore.ieee.org/servlet/opac?punumber=8573
    DOI
    https://doi.org/10.1109/FUZZ.2003.1206564
    Copyright Statement
    © 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    Publication URI
    http://hdl.handle.net/10072/24443
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    • Conference outputs

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