Detection of melanoma through image recognition and artificial neural networks
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- Marín C., Alférez G.H., Córdova J., González V. (2015) Detection of melanoma through image recognition and artificial neural networks. In: Jaffray D. (eds) World Congress on Medical Physics and Biomedical Engineering, June 7-12, 2015, Toronto, Canada. IFMBE Proceedings, vol 51. Springer, Cham
The incidence of malignant melanoma has signifi- cantly increased in the last four decades. Dermatologists are rarely present in rural or remote areas to perform an early de- tection of malignant melanoma. Our contribution is a low cost software that automatically and objectively differentiates be- tween a melanoma lesion and a benign nevus in a simple, non- invasive manner. Our approach is based on the “ABCDE” classi- fication of lesions, image processing, and artificial neural net- works. The software was developed using images of previously diagnosed malignant melanomas and non-malignant suspicious moles, obtaining a sensibility of 76.56% and a specificity of 87.58%.
KeywordsCutaneous neoplasia Skin cancer Melanoma Artificial intelligence Artificial Neural Networks Image Processing
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