Open Science Research Excellence
%0 Journal Article
%A Rahil Garnavi and  Mohammad Aldeen and  M. Emre Celebi and  Alauddin Bhuiyan and  Constantinos Dolianitis and George Varigos
%D 2011 
%J  International Journal of Biomedical and Biological Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 55, 2011
%T Automatic Segmentation of Dermoscopy Images Using Histogram Thresholding on Optimal Color Channels
%U http://waset.org/publications/3079
%V 55
%X Automatic segmentation of skin lesions is the first step
towards development of a computer-aided diagnosis of melanoma.
Although numerous segmentation methods have been developed,
few studies have focused on determining the most discriminative
and effective color space for melanoma application. This paper
proposes a novel automatic segmentation algorithm using color space
analysis and clustering-based histogram thresholding, which is able to
determine the optimal color channel for segmentation of skin lesions.
To demonstrate the validity of the algorithm, it is tested on a set of 30
high resolution dermoscopy images and a comprehensive evaluation
of the results is provided, where borders manually drawn by four
dermatologists, are compared to automated borders detected by the
proposed algorithm. The evaluation is carried out by applying three
previously used metrics of accuracy, sensitivity, and specificity and
a new metric of similarity. Through ROC analysis and ranking the
metrics, it is shown that the best results are obtained with the X and
XoYoR color channels which results in an accuracy of approximately
97%. The proposed method is also compared with two state-ofthe-
art skin lesion segmentation methods, which demonstrates the
effectiveness and superiority of the proposed segmentation method.
%P 275 - 283