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Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts
Nasopharyngeal carcinoma is one of the malignant neoplasm with high incidence in China and south-east Asia. Ki-67 protein is strictly associated with cell proliferation and malignant degree. Cells with higher Ki-67 expression are always sensitive to chemotherapy and radiotherapy, the assessment of w...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999801/ https://www.ncbi.nlm.nih.gov/pubmed/27562647 http://dx.doi.org/10.1038/srep32127 |
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author | Shi, Peng Zhong, Jing Hong, Jinsheng Huang, Rongfang Wang, Kaijun Chen, Yunbin |
author_facet | Shi, Peng Zhong, Jing Hong, Jinsheng Huang, Rongfang Wang, Kaijun Chen, Yunbin |
author_sort | Shi, Peng |
collection | PubMed |
description | Nasopharyngeal carcinoma is one of the malignant neoplasm with high incidence in China and south-east Asia. Ki-67 protein is strictly associated with cell proliferation and malignant degree. Cells with higher Ki-67 expression are always sensitive to chemotherapy and radiotherapy, the assessment of which is beneficial to NPC treatment. It is still challenging to automatically analyze immunohistochemical Ki-67 staining nasopharyngeal carcinoma images due to the uneven color distributions in different cell types. In order to solve the problem, an automated image processing pipeline based on clustering of local correlation features is proposed in this paper. Unlike traditional morphology-based methods, our algorithm segments cells by classifying image pixels on the basis of local pixel correlations from particularly selected color spaces, then characterizes cells with a set of grading criteria for the reference of pathological analysis. Experimental results showed high accuracy and robustness in nucleus segmentation despite image data variance. Quantitative indicators obtained in this essay provide a reliable evidence for the analysis of Ki-67 staining nasopharyngeal carcinoma microscopic images, which would be helpful in relevant histopathological researches. |
format | Online Article Text |
id | pubmed-4999801 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49998012016-09-01 Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts Shi, Peng Zhong, Jing Hong, Jinsheng Huang, Rongfang Wang, Kaijun Chen, Yunbin Sci Rep Article Nasopharyngeal carcinoma is one of the malignant neoplasm with high incidence in China and south-east Asia. Ki-67 protein is strictly associated with cell proliferation and malignant degree. Cells with higher Ki-67 expression are always sensitive to chemotherapy and radiotherapy, the assessment of which is beneficial to NPC treatment. It is still challenging to automatically analyze immunohistochemical Ki-67 staining nasopharyngeal carcinoma images due to the uneven color distributions in different cell types. In order to solve the problem, an automated image processing pipeline based on clustering of local correlation features is proposed in this paper. Unlike traditional morphology-based methods, our algorithm segments cells by classifying image pixels on the basis of local pixel correlations from particularly selected color spaces, then characterizes cells with a set of grading criteria for the reference of pathological analysis. Experimental results showed high accuracy and robustness in nucleus segmentation despite image data variance. Quantitative indicators obtained in this essay provide a reliable evidence for the analysis of Ki-67 staining nasopharyngeal carcinoma microscopic images, which would be helpful in relevant histopathological researches. Nature Publishing Group 2016-08-26 /pmc/articles/PMC4999801/ /pubmed/27562647 http://dx.doi.org/10.1038/srep32127 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Shi, Peng Zhong, Jing Hong, Jinsheng Huang, Rongfang Wang, Kaijun Chen, Yunbin Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts |
title | Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts |
title_full | Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts |
title_fullStr | Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts |
title_full_unstemmed | Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts |
title_short | Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts |
title_sort | automated ki-67 quantification of immunohistochemical staining image of human nasopharyngeal carcinoma xenografts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999801/ https://www.ncbi.nlm.nih.gov/pubmed/27562647 http://dx.doi.org/10.1038/srep32127 |
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