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


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


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

Magdalena Michalska  mmagamichalska@gmail.com
  Poland
Oksana Boyko 
Danylo Halytsky Lviv National Medical University, Department of Medical Informatics  Ukraine
http://orcid.org/0000-0002-8810-8969