Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/20.500.12258/18092
Title: Method of cleaning hair structures for intellectual image classification of skin neoplasms
Authors: Lyakhova, U. A.
Ляхова, У. А.
Lyakhov, P. A.
Ляхов, П. А.
Keywords: Convolutional neural networks;Dermatoscopic images;Digital image processing;Hair removal;Medical image processing;;Melanoma;Pigmented skin lesions
Issue Date: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Lyakhova, U. A.; Lyakhov, P. A. Method of cleaning hair structures for intellectual image classification of skin neoplasms // Proceedings - 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2021. - 2021. - Стр.: 20 - 23. - Номер статьи 9455057
Series/Report no.: Proceedings - 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2021
Abstract: The main problem in the application of artificial intelligence in the field of dermatology is the low level of accuracy of recognition and classification systems. This paper proposes a method for identifying and cleaning hair, as well as evaluating the effectiveness of the method using a pre-trained neural network. When examining pigmented lesions, the presence of hair in images can obscure important diagnostic information, reducing the effectiveness and quality of examination results. This method allows the preparation of dermatoscopic images for further automated classification and diagnosis of pigmented skin lesions. Modeling was carried out using the MatLab R2019b software package on clinical dermatoscopic images from the international open archive ISIC Melanoma Project. The proposed method made it possible to achieve the accuracy of recognition of images of pigmented skin lesions in 10 diagnostically important categories up to 80.81%. The use of neural network classification systems for dermatoscopic images of pigmented skin formations with a preliminary stage of hair removal will allow specialists to increase the efficiency and speed of diagnosis and start treatment of the disease at an earlier stage
URI: http://hdl.handle.net/20.500.12258/18092
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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