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A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion
Vaginitis is one of the commonly encountered diseases of female reproductive tract infections. The clinical diagnosis mainly relies on manual observation under a microscope. There has been some investigation on the classification of vaginitis diseases based on computer-aided diagnosis to reduce the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840418/ https://www.ncbi.nlm.nih.gov/pubmed/35161875 http://dx.doi.org/10.3390/s22031132 |
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author | Zhao, Kongya Gao, Peng Liu, Sunxiangyu Wang, Ying Li, Guitao Wang, Youzheng |
author_facet | Zhao, Kongya Gao, Peng Liu, Sunxiangyu Wang, Ying Li, Guitao Wang, Youzheng |
author_sort | Zhao, Kongya |
collection | PubMed |
description | Vaginitis is one of the commonly encountered diseases of female reproductive tract infections. The clinical diagnosis mainly relies on manual observation under a microscope. There has been some investigation on the classification of vaginitis diseases based on computer-aided diagnosis to reduce the workload of clinical laboratory staff. However, the studies only using RGB images limit the development of vaginitis diagnosis. Through multi-spectral technology, we propose a vaginitis classification algorithm based on multi-spectral image feature layer fusion. Compared with the traditional RGB image, our approach improves the classification accuracy by 11.39%, precision by 15.82%, and recall by 27.25%. Meanwhile, we prove that the level of influence of each spectrum on the disease is distinctive, and the subdivided spectral image is more conducive to the image analysis of vaginitis disease. |
format | Online Article Text |
id | pubmed-8840418 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88404182022-02-13 A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion Zhao, Kongya Gao, Peng Liu, Sunxiangyu Wang, Ying Li, Guitao Wang, Youzheng Sensors (Basel) Article Vaginitis is one of the commonly encountered diseases of female reproductive tract infections. The clinical diagnosis mainly relies on manual observation under a microscope. There has been some investigation on the classification of vaginitis diseases based on computer-aided diagnosis to reduce the workload of clinical laboratory staff. However, the studies only using RGB images limit the development of vaginitis diagnosis. Through multi-spectral technology, we propose a vaginitis classification algorithm based on multi-spectral image feature layer fusion. Compared with the traditional RGB image, our approach improves the classification accuracy by 11.39%, precision by 15.82%, and recall by 27.25%. Meanwhile, we prove that the level of influence of each spectrum on the disease is distinctive, and the subdivided spectral image is more conducive to the image analysis of vaginitis disease. MDPI 2022-02-02 /pmc/articles/PMC8840418/ /pubmed/35161875 http://dx.doi.org/10.3390/s22031132 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhao, Kongya Gao, Peng Liu, Sunxiangyu Wang, Ying Li, Guitao Wang, Youzheng A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion |
title | A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion |
title_full | A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion |
title_fullStr | A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion |
title_full_unstemmed | A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion |
title_short | A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion |
title_sort | vaginitis classification method based on multi-spectral image feature fusion |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840418/ https://www.ncbi.nlm.nih.gov/pubmed/35161875 http://dx.doi.org/10.3390/s22031132 |
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