Enhanced K-mean Using Evolutionary Algorithms for Melanoma Detection and Segmentation in Skin Images

Abstract

See, stats, and : https : / / www . researchgate . net / publication / 322156328 Enhanced -mean Algorithms Segmentation Article DOI : 10 . 14569 / IJACSA. 2017 . 081263 CITATIONS 0 READS 29 2 : Some : Enhanced - mean Images face Asmaa University 4 SEE Esraa University 1 SEE All . The . Abstract—Nowadays , Melanoma has become one of the most significant public health concerns . Malignant Melanoma (MM) is considered the most rapidly spreading type of skin cancer . In this paper , we have built models for detection , segmentation , and classification of Melanoma in skin images using evolutionary algorithms . The first step was to enhance the K - mean algorithm by using two kinds of Evolutionary Algorithms : a Genetic Algo - rithm and the Particle Swarm Algorithm . Then the Enhanced Algorithms and the default k - mean separately were used to do detection and segmentation of skin cancer images . Then a feature extraction step was applied on the segmented images . Finally , the classification step was done by using two predictive models . The first model was built using a Neural Network back - propagation and the other one using some threshold values for some selected features . The results showed a high accuracy using Neural Back - propagation for the Enhanced K - mean by using a Genetic Algorithm , which achieved 87 . 5% .