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    A New ROI-Based performance evaluation method for image denoising using the Squared Eigenfunctions of the Schrödinger Operator

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    EMBC18_ROI_Deoising_EMBC2018_Chahid1.pdf
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    Type
    Conference Paper
    Authors
    Chahid, Abderrazak cc
    Serrai, Hacene
    Achten, Eric
    Laleg-Kirati, Taous-Meriem cc
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2018-11-16
    Online Publication Date
    2018-11-16
    Print Publication Date
    2018-07
    Permanent link to this record
    http://hdl.handle.net/10754/630099
    
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    Abstract
    In this paper a new Region Of Interest (ROI) characterization for image denoising performance evaluation is proposed. This technique consists of balancing the contrast between the dark and bright ROIs, in Magnetic Resonance (MR) images, to track the noise removal. It achieves an optimal compromise between removal of noise and preservation of image details. The ROI technique has been tested using synthetic MRI images from the BrainWeb database. Moreover, it has been applied to a recently developed denoising method called Semi-Classical Signal Analysis (SCSA). The SCSA decomposes the image into the squared eigenfunctions of the Schrödinger operator where a soft threshold h is used to remove the noise. The results obtained using real MRI data suggest that this method is suitable for real medical image processing evaluation where the noise-free image is not available.
    Citation
    Chahid A, Serrai H, Achten E, Laleg-Kirati T-M (2018) A New ROI-Based performance evaluation method for image denoising using the Squared Eigenfunctions of the Schrödinger Operator. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Available: http://dx.doi.org/10.1109/EMBC.2018.8513615.
    Sponsors
    Research reported in this publication was supported by King Abdullah University of Science and Technology.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
    Conference/Event name
    2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
    DOI
    10.1109/EMBC.2018.8513615
    Additional Links
    https://ieeexplore.ieee.org/document/8513615
    ae974a485f413a2113503eed53cd6c53
    10.1109/EMBC.2018.8513615
    Scopus Count
    Collections
    Conference Papers; Electrical and Computer Engineering Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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