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Classification of Skin Cancers using Radial basis Function Network

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Sasirooba Thirumavalavan, Sasikala Jayaraman
10.5120/ijca2016911733

Sasirooba Thirumavalavan and Sasikala Jayaraman. Classification of Skin Cancers using Radial basis Function Network. International Journal of Computer Applications 151(4):19-22, October 2016. BibTeX

@article{10.5120/ijca2016911733,
	author = {Sasirooba Thirumavalavan and Sasikala Jayaraman},
	title = {Classification of Skin Cancers using Radial basis Function Network},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {151},
	number = {4},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {19-22},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume151/number4/26221-2016911733},
	doi = {10.5120/ijca2016911733},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

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.

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Keywords

denoising, segmentation, radial basis function network.