Abstract
Melanoma is a type of skin cancer having high survival rate with early stage detection. Dermoscopy images are used for the detection of melanoma. This work is planned to develop a novel technique for segmenting skin lesions from the dermoscopy images is analyzed and implemented. The method implemented is adaptive active contour segmentation. The results obtained by this method are analyzed by using various metrics. From this, the adaptive active contour-based segmentation provides a better segmentation results when compared with other methods with average error rate of 0.13. So, the adaptive active contour segmentation method is used along with hair removal technique, and this segmented image will be used for the classification, i.e., whether melanoma is present or not.
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Abhilash, K.S., Kumar, P.S.S., Ravindran, Z., Rahman, A.N. (2021). Adaptive Active Contour Segmentation for Melanoma Diagnosis from Dermoscopy Images. In: Dash, S.S., Panigrahi, B.K., Das, S. (eds) Sixth International Conference on Intelligent Computing and Applications . Advances in Intelligent Systems and Computing, vol 1369. Springer, Singapore. https://doi.org/10.1007/978-981-16-1335-7_12
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DOI: https://doi.org/10.1007/978-981-16-1335-7_12
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