A REVIEW ON DIAGNOSIS OF MALIGNANT MELANOMA FROM BENIGN LESION BY USING BPNN AND ABCD RULE PARAMETERS

Abstract

One of the most dangerous diseases is Human Cancer, it is caused by instability of the multiple molecular alterations in the genetic. The most common one among the different forms of human cancer is the skin cancer. With help of different techniques like segmentation and feature extraction the skin cancer can be identified and analyzed at the early stage. The malignant melanoma skin cancer which occurs due to the high concentration of the melanocytic cells present beneath the skin is demonstrated in this paper. In this paper, for detecting of the malignant melanoma skin cancer the ABCD rule dermoscopy technology is used. First, the Image Acquisition technique then the pre-processing, segmentation, skin Feature Selection determines lesion characterization and classification methods are the several techniques used to find melanoma skin lesion. By digital image processing methods like border detection, color, symmetry detection and diameter detection the feature extraction is done and for the extraction of the texture-based feature LBP is used. As a classifier ANN is used in this proposed method. Finally, to classify the benign or malignant stage the Back Propagation Neural Network is used.