TELKOMNIKA Telecommunication, Computing, Electronics and Control
A machine learning approach for the recognition of melanoma skin cancer on macroscopic images

TELKOMNIKA Telecommunication, Computing, Electronics and Control
A machine learning approach for the recognition of melanoma skin cancer on macroscopic images

Artificial intelligence
Image processing
Machine learning
Melanoma
Skin cancer

In the last years, computer vision systems for the detection of skin cancer have been
proposed, especially using machine learning techniques for the classification of the

disease and features based on the ABCD dermatology criterion, which gives infor-
mation on the status of the skin lesion based on static properties such as geometry,

color, and texture, making it an appropriate criterion for medical diagnosis systems

that work through images. This paper proposes a novel skin cancer classification sys-
tem that works on images taken from a standard camera and studies the impact on

the results of the smoothed bootstrapping, which was used to augment the original

dataset. Eight classifiers with different topologies (KNN, ANN, and SVM) were com-
pared, with and without data augmentation, showing that the classifier with the highest

performance as well as the most balanced one was the ANN with data augmentation,
achieving an AUC of 87.1%, which saw an improvement from an AUC of 84.3% of
the ANN trained with the original dataset.

Jairo Hurtado, Francisco Reales

http://journal.uad.ac.id/index.php/TELKOMNIKA

Jan 20, 2021

peri irawan

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