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Staining Pattern Classification of Antinuclear Autoantibodies Based on Block Segmentation in Indirect Immunofluorescence Images
Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256175/ https://www.ncbi.nlm.nih.gov/pubmed/25474260 http://dx.doi.org/10.1371/journal.pone.0113132 |
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author | Li, Jiaqian Tseng, Kuo-Kun Hsieh, Zu Yi Yang, Ching Wen Huang, Huang-Nan |
author_facet | Li, Jiaqian Tseng, Kuo-Kun Hsieh, Zu Yi Yang, Ching Wen Huang, Huang-Nan |
author_sort | Li, Jiaqian |
collection | PubMed |
description | Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image) with a total accuracy of about 94.62%. |
format | Online Article Text |
id | pubmed-4256175 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-42561752014-12-11 Staining Pattern Classification of Antinuclear Autoantibodies Based on Block Segmentation in Indirect Immunofluorescence Images Li, Jiaqian Tseng, Kuo-Kun Hsieh, Zu Yi Yang, Ching Wen Huang, Huang-Nan PLoS One Research Article Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image) with a total accuracy of about 94.62%. Public Library of Science 2014-12-04 /pmc/articles/PMC4256175/ /pubmed/25474260 http://dx.doi.org/10.1371/journal.pone.0113132 Text en © 2014 Li et al This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Li, Jiaqian Tseng, Kuo-Kun Hsieh, Zu Yi Yang, Ching Wen Huang, Huang-Nan Staining Pattern Classification of Antinuclear Autoantibodies Based on Block Segmentation in Indirect Immunofluorescence Images |
title | Staining Pattern Classification of Antinuclear Autoantibodies Based on Block
Segmentation in Indirect Immunofluorescence Images |
title_full | Staining Pattern Classification of Antinuclear Autoantibodies Based on Block
Segmentation in Indirect Immunofluorescence Images |
title_fullStr | Staining Pattern Classification of Antinuclear Autoantibodies Based on Block
Segmentation in Indirect Immunofluorescence Images |
title_full_unstemmed | Staining Pattern Classification of Antinuclear Autoantibodies Based on Block
Segmentation in Indirect Immunofluorescence Images |
title_short | Staining Pattern Classification of Antinuclear Autoantibodies Based on Block
Segmentation in Indirect Immunofluorescence Images |
title_sort | staining pattern classification of antinuclear autoantibodies based on block
segmentation in indirect immunofluorescence images |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256175/ https://www.ncbi.nlm.nih.gov/pubmed/25474260 http://dx.doi.org/10.1371/journal.pone.0113132 |
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