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Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks
Recent years have seen a growing awareness of the role the immune system plays in successful cancer treatment, especially in novel therapies like immunotherapy. The characterization of the immunological composition of tumors and their micro-environment is thus becoming a necessity. In this paper we...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6462181/ https://www.ncbi.nlm.nih.gov/pubmed/30993030 http://dx.doi.org/10.7717/peerj.6335 |
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author | Aprupe, Lilija Litjens, Geert Brinker, Titus J. van der Laak, Jeroen Grabe, Niels |
author_facet | Aprupe, Lilija Litjens, Geert Brinker, Titus J. van der Laak, Jeroen Grabe, Niels |
author_sort | Aprupe, Lilija |
collection | PubMed |
description | Recent years have seen a growing awareness of the role the immune system plays in successful cancer treatment, especially in novel therapies like immunotherapy. The characterization of the immunological composition of tumors and their micro-environment is thus becoming a necessity. In this paper we introduce a deep learning-based immune cell detection and quantification method, which is based on supervised learning, i.e., the input data for training comprises labeled images. Our approach objectively deals with staining variation and staining artifacts in immunohistochemically stained lung cancer tissue and is as precise as humans. This is evidenced by the low cell count difference to humans of 0.033 cells on average. This method, which is based on convolutional neural networks, has the potential to provide a new quantitative basis for research on immunotherapy. |
format | Online Article Text |
id | pubmed-6462181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64621812019-04-16 Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks Aprupe, Lilija Litjens, Geert Brinker, Titus J. van der Laak, Jeroen Grabe, Niels PeerJ Oncology Recent years have seen a growing awareness of the role the immune system plays in successful cancer treatment, especially in novel therapies like immunotherapy. The characterization of the immunological composition of tumors and their micro-environment is thus becoming a necessity. In this paper we introduce a deep learning-based immune cell detection and quantification method, which is based on supervised learning, i.e., the input data for training comprises labeled images. Our approach objectively deals with staining variation and staining artifacts in immunohistochemically stained lung cancer tissue and is as precise as humans. This is evidenced by the low cell count difference to humans of 0.033 cells on average. This method, which is based on convolutional neural networks, has the potential to provide a new quantitative basis for research on immunotherapy. PeerJ Inc. 2019-04-10 /pmc/articles/PMC6462181/ /pubmed/30993030 http://dx.doi.org/10.7717/peerj.6335 Text en ©2019 Aprupe et al. http://creativecommons.org/licenses/by/4.0/ 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, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Oncology Aprupe, Lilija Litjens, Geert Brinker, Titus J. van der Laak, Jeroen Grabe, Niels Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks |
title | Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks |
title_full | Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks |
title_fullStr | Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks |
title_full_unstemmed | Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks |
title_short | Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks |
title_sort | robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6462181/ https://www.ncbi.nlm.nih.gov/pubmed/30993030 http://dx.doi.org/10.7717/peerj.6335 |
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