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

Magdalena Michalska; Oksana Boyko

doi:10.35784/iapgos.1569

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Published: Jun 30, 2020

DOI: https://doi.org/10.35784/iapgos.1569

Issue Vol. 10 No. 2 (2020)

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

https://doi.org/10.35784/iapgos.1569

Authors

Magdalena Michalska

mmagamichalska@gmail.com

Lublin University of Technology, Poland

Oksana Boyko

oxana_bojko@ukr.net

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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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

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