Segmentation of Skin Lesions from Digital Images using Texture Distinctiveness with Neural Network

Abstract: Melanoma is the deadliest form of skin cancer. Incidence rates of melanoma have been increasing, but survival rates are high if detected early. Inorder to reduce the costs for dermatologists to screen every patient, there is a need for an automated melanoma screening system. In this paper, texture distinctiveness lesion segmentation algorithm is used. Dermatologists diagnose malignancy in skin lesions based on their extensive training, experience from previous diagnoses, and their access to vast amounts of medical research. Experience and training-based learning is an important characteristic of neural networks. Therefore a back propagation neural network is used with texture distinctiveness lesion segmentation algorithm. The proposed framework shows higher segmentation accuracy.

Keywords: Melanoma, segmentation, skin cancer, texture, neural network