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    Please use this identifier to cite or link to this item: http://140.128.103.80:8080/handle/310901/21428


    Title: Adaptive automatic segmentation of HEp-2 cells in indirect immunofluorescence images
    Authors: Huang, Y.-L.a , Jao, Y.-L.a, Hsieh, T.-Y.b, Chung, C.-W.a
    Contributors: Department of Computer Science, Tunghai University
    Date: 2008-06-11
    Issue Date: 2013-05-14T09:06:19Z (UTC)
    Publisher: Taichung; Taiwan
    Abstract: Indirect immunofluorescence (IIF) with HEp-2 cells is used for the detection of antinuclear autoantibodies (ANA) in systemic autoimmune diseases. An automatic inspection system for ANA testing can be divided into HEp-2 cell detection, fluorescence pattern classification and computer aided diagnosis phases. This study focused on the first phase of cell detecting and locating. This study presented an adaptive edged-based segmentation method for automatically detecting outlines of fluorescence cells in IIF images. The proposed method evaluated 2573 cells with six distinct fluorescence patterns from 45 images. The results of computer simulations revealed that the proposed method always identified cell outlines as were obtained by manual sketched. Such a method provides robust and fast automatic segmentation of HEp-2 fluorescent patterns in ANA testing. ? 2008 IEEE.
    Relation: Proceedings - IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing
    2008, Article number4545795, Pages 418-422
    Appears in Collections:[資訊工程學系所] 會議論文

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