Segmentation And Automatic Classification Of Skin Lesion Using Neural Networks
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2021 by IJETT Journal|
|Year of Publication : 2021|
|Authors : Er. Simrandeep Singh
|DOI : 10.14445/22315381/IJETT-V69I1P218|
MLA Style: Er. Simrandeep Singh. "Segmentation And Automatic Classification Of Skin Lesion Using Neural Networks" International Journal of Engineering Trends and Technology 69.1(2021):116-120.
APA Style:Er. Simrandeep Singh. Segmentation And Automatic Classification Of Skin Lesion Using Neural Networks International Journal of Engineering Trends and Technology, 69(1), 116-120.
Melanoma is a lethal disease often impossible to cure if detected at later stages. To save a person, it is necessary to detect melanoma at earlier stages because melanoma treatment is detected at prior stages. Due to several reasons, there is a need for an automated system to detect melanoma. An automated system for the segmentation and the skin lesion classification is proposed using the artificial neural network. Image segmentation is carried out to bifurcate input image into different clusters. In this proposed methodology, the Fuzzy C Means algorithm is used for the pre-segmentation, and then Gaussian Mixture Model is used for the modeling. The results of the Gaussian mixture model are not as efficient up to the desired level. Artificial Neural Networks are used to achieve the highest accuracy, and their accuracy is checked by using the parameters of sensitivity and specificity.
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Skin Cancer, Melanoma, Gaussian Mixture Model, Artificial Neural Network, Innovation.