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  • A prelimary approach for the automated recognition of malignant melanoma
    Zagrouba, Ezzeddine ; Barhoumi, Walid
    In this work, we are motivated by the desire to classify skin lesions as malignants or benigns from color photographic slides of the lesions. Thus, we use color images of skin lesions, image ... processing techniques and artificial neural network classifier to distinguish melanoma from benign pigmented lesions. As the first step of the data set analysis, a preprocessing sequence is implemented to remove noise and undesired structures from the color image. Second, an automated segmentation approach localizes suspicious lesion regionsby region growing after a preliminary step based on fuzzy sets. Then, we rely on quantitative image analysis to measure a series of candidate attributes hoped to contain enough information to differentiate melanomas frombenign lesions. At last, the selected features are supplied to an artificial neural network for classification of tumor lesion as malignant or benign. For a preliminary balanced training/testing set, our approach is able to obtain 79.1% of correct classification of malignant and benign lesions on real skin lesion images.
    Vir: Image analysis & stereology : official journal of the International Society for Stereology. - ISSN 1580-3139 (Vol. 23, no. 2, jun. 2004, str. 121-135)
    Vrsta gradiva - članek, sestavni del
    Leto - 2004
    Jezik - angleški
    COBISS.SI-ID - 20713945

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    Digitalna knjižnica Slovenije - dLib.si

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