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Detection of Melanoma Skin Cancer using Segmentation and Classification Algorithms

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IJCA Proceedings on National Conference on Information and Communication Technologies
© 2015 by IJCA Journal
NCICT 2015 - Number 2
Year of Publication: 2015
Authors:
I. S. Akila
Sumathi V.

I s Akila and Sumathi V.. Article: Detection of Melanoma Skin Cancer using Segmentation and Classification Algorithms. IJCA Proceedings on National Conference on Information and Communication Technologies NCICT 2015(2):1-4, September 2015. Full text available. BibTeX

@article{key:article,
	author = {I.s. Akila and Sumathi V.},
	title = {Article: Detection of Melanoma Skin Cancer using Segmentation and Classification Algorithms},
	journal = {IJCA Proceedings on National Conference on Information and Communication Technologies},
	year = {2015},
	volume = {NCICT 2015},
	number = {2},
	pages = {1-4},
	month = {September},
	note = {Full text available}
}

Abstract

Melanoma is the most dangerous skin cancer. It should be diagnosed early because of its aggressiveness. To diagnose melanoma earlier, skin lesion should be segmented accurately. To reduce the cost for specialists to screen every patient, there is a need of automated melanoma prescreening system to diagnose melanoma using images acquired in digital cameras. In this frame work, an automated melanoma prescreening system is proposed to diagnose melanoma skin cancer using Modified TDLS algorithm and SVM classifier. Representative texture distributions are obtained from texture vectors. The segmentation accuracy is improved by modification in TDLS algorithm. TD metric is calculated with lesion texture distributions only. The entire system is tested using MATLAB software.

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