Classification of Skin Cancers using Radial basis Function Network

Abstract

This paper suggests a model for classifying skin lesions into benign and malignant melanoma using radial basis function network (RBFN). The model initially converts the color image into gray image and then applies Median filter for removing thin hairs and other noises. It then segments the cancerous region through segmentation and then extracts features that represent the characteristics of the skin lesion. The RBFN then processes the computed features and classifies the skin lesion either as a benign or a malignant. The paper discusses with intermediate results on sample skin images and exhibits the elegant performance of the suggested model. General Termsimage processing, classification Keywords denoising, segmentation, radial basis function network.

Skin cancer diagnosis using artificial intelligence methods: a review of the most recent research

“…In 63 the authors proposed a model using a radial basis function network (RBFN) for diagnosing and classifying skin cancer. The first phase of the model is preprocessing by applying a median filter.…”