A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural network
In this study, we proposed a method to measure the epidermal thickness (ET) of skin based on deep convolutional neural network, which was used to determine the boundaries of skin surface and the ridge portion in dermal–epidermis junction (DEJ) in cross-section optical coherence tomography (OCT) imag...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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World Scientific Publishing
2021-01-01
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| Series: | Journal of Innovative Optical Health Sciences |
| Subjects: | |
| Online Access: | http://www.worldscientific.com/doi/epdf/10.1142/S1793545821400058 |
| _version_ | 1818455324472901632 |
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| author | Yongping Lin Dezi Li Wang Liu Zhaowei Zhong Zhifang Li Youwu He Shulian Wu |
| author_facet | Yongping Lin Dezi Li Wang Liu Zhaowei Zhong Zhifang Li Youwu He Shulian Wu |
| author_sort | Yongping Lin |
| collection | DOAJ |
| description | In this study, we proposed a method to measure the epidermal thickness (ET) of skin based on deep convolutional neural network, which was used to determine the boundaries of skin surface and the ridge portion in dermal–epidermis junction (DEJ) in cross-section optical coherence tomography (OCT) images of fingertip skin. The ET was calculated based on the row difference between the surface and the ridge top, which is determined by search the local maxima of boundary of the ridge portion. The results demonstrated that the region of ridge portion in DEJ was well determined and the ET measurement in this work can reduce the effect of the papillae valley in DEJ by 9.85%. It can be used for quantitative characterization of skin to differentiate the skin diseases. |
| first_indexed | 2024-12-14T22:08:58Z |
| format | Article |
| id | doaj.art-76c8c611b36846369e979bc7ca5ddd19 |
| institution | Directory Open Access Journal |
| issn | 1793-5458 1793-7205 |
| language | English |
| last_indexed | 2024-12-14T22:08:58Z |
| publishDate | 2021-01-01 |
| publisher | World Scientific Publishing |
| record_format | Article |
| series | Journal of Innovative Optical Health Sciences |
| spelling | doaj.art-76c8c611b36846369e979bc7ca5ddd192022-12-21T22:45:48ZengWorld Scientific PublishingJournal of Innovative Optical Health Sciences1793-54581793-72052021-01-011412140005-12140005-710.1142/S179354582140005810.1142/S1793545821400058A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural networkYongping Lin0Dezi Li1Wang Liu2Zhaowei Zhong3Zhifang Li4Youwu He5Shulian Wu6Fujian Provincial Key Laboratory of Optoelectronic Technology and Devices, School of Optoelectronic and Communication Engineering, Xiamen University of Technology, Xiamen 361024, P. R. ChinaKey Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian 350007, P. R. ChinaKey Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian 350007, P. R. ChinaKey Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian 350007, P. R. ChinaKey Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian 350007, P. R. ChinaKey Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian 350007, P. R. ChinaKey Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian 350007, P. R. ChinaIn this study, we proposed a method to measure the epidermal thickness (ET) of skin based on deep convolutional neural network, which was used to determine the boundaries of skin surface and the ridge portion in dermal–epidermis junction (DEJ) in cross-section optical coherence tomography (OCT) images of fingertip skin. The ET was calculated based on the row difference between the surface and the ridge top, which is determined by search the local maxima of boundary of the ridge portion. The results demonstrated that the region of ridge portion in DEJ was well determined and the ET measurement in this work can reduce the effect of the papillae valley in DEJ by 9.85%. It can be used for quantitative characterization of skin to differentiate the skin diseases.http://www.worldscientific.com/doi/epdf/10.1142/S1793545821400058epidermal thicknesscross-section oct imagesconvolutional neural network |
| spellingShingle | Yongping Lin Dezi Li Wang Liu Zhaowei Zhong Zhifang Li Youwu He Shulian Wu A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural network Journal of Innovative Optical Health Sciences epidermal thickness cross-section oct images convolutional neural network |
| title | A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural network |
| title_full | A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural network |
| title_fullStr | A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural network |
| title_full_unstemmed | A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural network |
| title_short | A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural network |
| title_sort | measurement of epidermal thickness of fingertip skin from oct images using convolutional neural network |
| topic | epidermal thickness cross-section oct images convolutional neural network |
| url | http://www.worldscientific.com/doi/epdf/10.1142/S1793545821400058 |
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