Author : Prema Gupta 1
Date of Publication :7th October 2020
Abstract: Skin cancer is the most common type of cancer, which affects the life of millions of people every year. About three million people are diagnosed with the disease every year in the United States alone. The rate of survival decreases steeply as the disease progresses. However, detection of skin cancer in the early stages is a difficult and expensive process. In this study, we propose a methodology that detects and identifies skin lesions as benign or malignant based upon images taken from general cameras. The images are segmented, features extracted by applying the rule and a Neural Network is trained to classify the lesions to a high degree of accuracy. artificial neural networks (ANNs) were used as diagnosis method for Skin cancer detection from magnetic resonance image. The detection of the cancer is performed in two stages: Preprocessing and enhancement in the first stage and segmentation and classification in the second stage which using different stages of statistical method; feature extraction which one of texture analysis and the last used this feature as input parameters to the feed-forward back propagation Artificial neural networks which designed by the neural networks toolbox in implemented all the result.
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