Diagnosis of Malignant Melanoma of Skin Cancer Types

Author
Keywords
Abstract
Malignant melanoma is a kind of skin cancer that begins in melanocytes. It can influence on the skin only, or it may expand to the bones and organs. It is less common, but more serious and aggressive than other types of skin cancer. Malignant Melanoma can happen anywhere on the skin, but it is widespread in certain locations such as the legs in women, the back and chest in men, the face, the neck, mouth, eyes, and genitals. In this paper, a proposed algorithm is designed for diagnosing malignant melanoma types by using digital image processing techniques. The algorithm consists of four steps: preprocessing, separation, features extraction, and diagnosis. A neural network (NN) used to diagnosis malignant melanoma types. The total accuracy of the neural network was 100% for training and 93% for testing. The evaluation of the algorithm is done by using sensitivity, specificity, and accuracy. The sensitivity of NN in diagnosing malignant melanoma types was 95.6%, while the specificity was 92.2% and the accuracy was 93.9%. The experimental results are acceptable.
Year of Publication
2017
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
4
Issue
Special Issue on 3D Medicine and Artificial Intelligence
Number
5
Number of Pages
44-49
Date Published
09/2017
ISSN Number
1989-1660
Citation Key
URL
http://www.ijimai.org/journal/sites/default/files/files/2016/12/ijimai20174_5_8_pdf_89993.pdf
DOI
10.9781/ijimai.2017.458
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