Skin Cancer Detection using Arificial Neural Network

Ekta Singhal, Shamik Tiwari

Abstract


Skin Cancer is most prevalent cancer in the light-Skinned population and it is generally caused by exposure to ultraviolet light. In this paper, an automatically skin cancer classification system is developed and the relationship of skin cancer image across the neural network are studied with different type of pre-processing. The collected image is feed into the system and image pre-processing is used for noise removal. Images are segment using thresholding. There is certain feature unique in skin cancer region these feature are extract using feature extraction technique. Mltilevel 2-D wavelet decomposition is used for feature extraction technique. These features are given to the input nodes of neural network. Back propagation neural network and radial basic neural network are used for classification purpose, which categories the given images into cancerous or non-cancerous.

Keywords: Skin cancer; Segmentation; thresholding; 2D Wavelet transform; BPN network; RBF network .


Full Text:

PDF


DOI: https://doi.org/10.26483/ijarcs.v6i1.2402

Refbacks

  • There are currently no refbacks.




Copyright (c) 2016 International Journal of Advanced Research in Computer Science