SELECTED APPLICATIONS OF DEEP NEURAL NETWORKS IN SKIN LESION DIAGNOSTIC | Zendy

Magdalena Michalska | Zendy

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SELECTED APPLICATIONS OF DEEP NEURAL NETWORKS IN SKIN LESION DIAGNOSTIC

Author(s) -

Magdalena Michalska

Publication year - 2021

Publication title -

informatyka automatyka pomiary w gospodarce i ochronie środowiska

Language(s) - English

Resource type - Journals

eISSN - 2391-6761

pISSN - 2083-0157

DOI - 10.35784/iapgos.2804

Subject(s) - skin lesion , artificial intelligence , computer science , segmentation , artificial neural network , dermatoscopy , pattern recognition (psychology) , lesion , melanoma diagnosis , melanoma , deep neural networks , multiclass classification , deep learning , selection (genetic algorithm) , skin cancer , machine learning , dermatology , medicine , pathology , cancer , support vector machine , cancer research

The article provides an overview of selected applications of deep neural networks in the diagnosis of skin lesions from human dermatoscopic images, including many dermatological diseases, including very dangerous malignant melanoma. The lesion segmentation process, features selection and classification was described. Application examples of binary and multiclass classification are given. The described algorithms have been widely used in the diagnosis of skin lesions. The effectiveness, specificity, and accuracy of classifiers were compared and analysed based on available datasets.

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