Detection of melanoma through image recognition and artificial neural networks

  • Cristofer Marín
  • Germán H. Alférez
  • Jency Córdova
  • Verenice González
Conference paper

DOI: 10.1007/978-3-319-19387-8_204

Part of the IFMBE Proceedings book series (IFMBE, volume 51)
Cite this paper as:
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

Abstract

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%.

Keywords

Cutaneous neoplasia Skin cancer Melanoma Artificial intelligence Artificial Neural Networks Image Processing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Cristofer Marín
    • 1
  • Germán H. Alférez
    • 1
  • Jency Córdova
    • 1
  • Verenice González
    • 1
  1. 1.Universidad de MontemorelosMontemorelosMexico

Personalised recommendations