Abstract
Most common and deadly type of cancer is Skin cancer. The destructive kind of cancers in skin is Melanoma as well as it can be identified at the initial stage and can be cured completely. For the diagnosis of melanoma, the identification of the melanocytes in the area of epidermis is an essential stage. In this paper the watershed segmentation method is implemented for segmentation. The extracted segments are subjected to feature extraction. The features extracted are shape, ABCD rule and GLCM. The extracted features are then used for classification. The classifiers are kNN (k Nearest Neighbor), Random Forest and SVM (Support Vector Machine). Among different classifiers, the SVM classifier provided better results for the skin lesions classification.
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Murugan, A., Nair, S.H. & Kumar, K.P.S. Detection of Skin Cancer Using SVM, Random Forest and kNN Classifiers. J Med Syst 43, 269 (2019). https://doi.org/10.1007/s10916-019-1400-8
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DOI: https://doi.org/10.1007/s10916-019-1400-8