AN OVERVIEW OF CLASSIFICATION METHODS FROM DERMOSCOPY IMAGES IN SKIN LESION DIAGNOSTIC

Magdalena Michalska

mmagamichalska@gmail.com
Lublin University of Technology (Poland)

Oksana Boyko


Danylo Halytsky Lviv National Medical University, Department of Medical Informatics (Ukraine)
http://orcid.org/0000-0002-8810-8969

Abstract

The article contains a review of selected classification methods of dermatoscopic images with human skin lesions, taking into account various stages of dermatological disease. The described algorithms are widely used in the diagnosis of skin lesions, such as artificial neural networks (CNN, DCNN), random forests, SVM, kNN classifier, AdaBoost MC and their modifications. The effectiveness, specificity and accuracy of classifications based on the same data sets were also compared and analyzed.


Keywords:

dermatoscopic images, classification methods, neural networks, SVM, skin cancer, skin lesions

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Published
2020-06-30

Cited by

Michalska, M., & Boyko, O. (2020). AN OVERVIEW OF CLASSIFICATION METHODS FROM DERMOSCOPY IMAGES IN SKIN LESION DIAGNOSTIC. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 10(2), 36–39. https://doi.org/10.35784/iapgos.1569

Authors

Magdalena Michalska 
mmagamichalska@gmail.com
Lublin University of Technology Poland

Authors

Oksana Boyko 

Danylo Halytsky Lviv National Medical University, Department of Medical Informatics Ukraine
http://orcid.org/0000-0002-8810-8969

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