An Improved Fuzzy C-means Algorithm learned wavelet network for segmentation of Dermoscopic image
نویسنده
چکیده
Dermoscopy is one of the major imaging aspects used in the skin lesions. This paper presentsa new tacticfor the segmentation of skin abrasionsin dermoscopic images based on fuzzy Cmeans algorithm learned wavelet network (WN). The WN offeredhere is a member of fixed-grid WNs that is designedwith no requirementof training. Fuzzy C-means techniqueis used to enhancethe network structure. In addition, this methodhas the capabilityto allocateone data point into more than one cluster. Since average shift can rapidlyand consistentlyobtain cluster centers, the absoluteschemeis capable of successfullyidentifyingareaswithin an image. The clusters are combinedinto lesion and surrounding skin region, yielding the segmented dermoscopy image. Then, the image is segmented and the skin lesions preciseedgeis decidedappropriately.Thesegmentation algorithm wererelated to 30 dermoscopic images and calculatedby means ofthe segmentation outcomeachievedby a skilled pathologist as the ground truth. Keywords-Dermoscopy,image segmentation, melanoma diagnosis, Fuzzy C-Means, wavelet network (WN).
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