System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network

Today, skin cancer is one of the most common malignant neoplasms in the human body. Diagnosis of pigmented lesions is challenging even for experienced dermatologists due to the wide range of morphological manifestations. Artificial intelligence technologies are capable of equaling and even surpassin...

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मुख्य लेखकों:	Lyakhov, P. A., Ляхов, П. А., Lyakhova, U. A., Ляхова, У. А., Nagornov, N. N., Нагорнов, Н. Н.
स्वरूप:	Статья
भाषा:	English
प्रकाशित:	MDPI 2022
विषय:	Pattern recognition Pigmented skin lesions Convolutional neural networks Dermatoscopic images Digital image processing Hair removal Heterogeneous data Melanoma Metadata Multimodal neural networks
ऑनलाइन पहुंच:	https://dspace.ncfu.ru/handle/20.500.12258/19431
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spelling	ir-20.500.12258-194312022-05-24T07:25:09Z System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network Lyakhov, P. A. Ляхов, П. А. Lyakhova, U. A. Ляхова, У. А. Nagornov, N. N. Нагорнов, Н. Н. Pattern recognition Pigmented skin lesions Convolutional neural networks Dermatoscopic images Digital image processing Hair removal Heterogeneous data Melanoma Metadata Multimodal neural networks Today, skin cancer is one of the most common malignant neoplasms in the human body. Diagnosis of pigmented lesions is challenging even for experienced dermatologists due to the wide range of morphological manifestations. Artificial intelligence technologies are capable of equaling and even surpassing the capabilities of a dermatologist in terms of efficiency. The main problem of implementing intellectual analysis systems is low accuracy. One of the possible ways to increase this indicator is using stages of preliminary processing of visual data and the use of heterogeneous data. The article proposes a multimodal neural network system for identifying pigmented skin lesions with a preliminary identification, and removing hair from dermatoscopic images. The novelty of the proposed system lies in the joint use of the stage of preliminary cleaning of hair structures and a multimodal neural network system for the analysis of heterogeneous data. The accuracy of pigmented skin lesions recognition in 10 diagnostically significant categories in the proposed system was 83.6%. The use of the proposed system by dermatologists as an auxiliary diagnostic method will minimize the impact of the human factor, assist in making medical decisions, and expand the possibilities of early detection of skin cancer. 2022-04-19T08:49:30Z 2022-04-19T08:49:30Z 2022 Статья Lyakhov, P. A., Lyakhova, U. A., Nagornov, N. N. System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network // Cancers. - 2022. - Том 14. - Выпуск 7. - Номер статьи 1819. - DOI10.3390/cancers14071819 http://hdl.handle.net/20.500.12258/19431 en Cancers application/pdf application/pdf MDPI
institution	СКФУ
collection	Репозиторий
language	English
topic	Pattern recognition Pigmented skin lesions Convolutional neural networks Dermatoscopic images Digital image processing Hair removal Heterogeneous data Melanoma Metadata Multimodal neural networks
spellingShingle	Pattern recognition Pigmented skin lesions Convolutional neural networks Dermatoscopic images Digital image processing Hair removal Heterogeneous data Melanoma Metadata Multimodal neural networks Lyakhov, P. A. Ляхов, П. А. Lyakhova, U. A. Ляхова, У. А. Nagornov, N. N. Нагорнов, Н. Н. System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
description	Today, skin cancer is one of the most common malignant neoplasms in the human body. Diagnosis of pigmented lesions is challenging even for experienced dermatologists due to the wide range of morphological manifestations. Artificial intelligence technologies are capable of equaling and even surpassing the capabilities of a dermatologist in terms of efficiency. The main problem of implementing intellectual analysis systems is low accuracy. One of the possible ways to increase this indicator is using stages of preliminary processing of visual data and the use of heterogeneous data. The article proposes a multimodal neural network system for identifying pigmented skin lesions with a preliminary identification, and removing hair from dermatoscopic images. The novelty of the proposed system lies in the joint use of the stage of preliminary cleaning of hair structures and a multimodal neural network system for the analysis of heterogeneous data. The accuracy of pigmented skin lesions recognition in 10 diagnostically significant categories in the proposed system was 83.6%. The use of the proposed system by dermatologists as an auxiliary diagnostic method will minimize the impact of the human factor, assist in making medical decisions, and expand the possibilities of early detection of skin cancer.
format	Статья
author	Lyakhov, P. A. Ляхов, П. А. Lyakhova, U. A. Ляхова, У. А. Nagornov, N. N. Нагорнов, Н. Н.
author_facet	Lyakhov, P. A. Ляхов, П. А. Lyakhova, U. A. Ляхова, У. А. Nagornov, N. N. Нагорнов, Н. Н.
author_sort	Lyakhov, P. A.
title	System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
title_short	System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
title_full	System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
title_fullStr	System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
title_full_unstemmed	System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
title_sort	system for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network
publisher	MDPI
publishDate	2022
url	https://dspace.ncfu.ru/handle/20.500.12258/19431
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System for the recognizing of pigmented skin lesions with fusion and analysis of heterogeneous data based on a multimodal neural network

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