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    National Tsing Hua University Institutional Repository > 電機資訊學院 > 電機工程學系 > 期刊論文 >  Ultrasonic liver tissues classification by fractal feature vector based on M-band wavelet transform


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/12389


    Title: Ultrasonic liver tissues classification by fractal feature vector based on M-band wavelet transform
    Authors: Lee, Wen-Li
    Chen, Yung-Chang
    Hsieh, Kai-Sheng
    教師: 陳永昌
    Date: 2003
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Relation: IEEE TRANSACTIONS ON MEDICAL IMAGING Volume: 22 Issue: 3 Pages: 382-392 Published: MAR 2003
    Keywords: Ultrasonic imaging
    Fractals
    Wavelet transforms
    Feature extraction
    Geometry
    Abstract: This paper describes the feasibility of selecting fractal feature vector based on M-band wavelet transform to classify ultrasonic liver images-normal liver, cirrhosis, and hepatoma. The proposed feature extraction algorithm is based on the spatial-frequency decomposition and fractal geometry. Various classification algorithms based on respective texture measurements and filter banks are presented and tested. Classifications for the three sets of ultrasonic liver images reveal that the fractal feature vector based on M-band wavelet transform is trustworthy. A hierarchical classifier, which is based on the proposed feature extraction algorithm is at least 96.7% accurate in the distinction between normal and abnormal liver images and is at least 93.6% accurate in the distinction between cirrhosis and hepatoma liver images. Additionally, the criterion for feature selection is specified and employed for performance comparisons herein.
    Relation Link: http://ieeexplore.ieee.org/Xplore/dynhome.jsp
    URI: http://nthur.lib.nthu.edu.tw/handle/987654321/12389
    Appears in Collections:[電機工程學系] 期刊論文
    [電腦與通訊科技研發中心] 期刊論文
    [腦科學研究中心] 期刊論文

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