The week's pick
Reseach Article
Detection of Melanoma Skin Cancer using Segmentation and Classification Algorithms
| National Conference on Information and Communication Technologies |
| Foundation of Computer Science USA |
| NCICT2015 - Number 2 |
| September 2015 |
| Authors: I.s. Akila, Sumathi V. |
| 2bef02ad-af19-4e26-8448-203bfa560813 |
I.s. Akila, Sumathi V. . Detection of Melanoma Skin Cancer using Segmentation and Classification Algorithms. National Conference on Information and Communication Technologies. NCICT2015, 2 (September 2015), 1-4.
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.
References
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