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...
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PeerJ Inc.
2019-04-01
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Online Access: | https://peerj.com/articles/6335.pdf |
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author | Lilija Aprupe Geert Litjens Titus J. Brinker Jeroen van der Laak Niels Grabe |
author_facet | Lilija Aprupe Geert Litjens Titus J. Brinker Jeroen van der Laak Niels Grabe |
author_sort | Lilija Aprupe |
collection | DOAJ |
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. |
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institution | Directory Open Access Journal |
issn | 2167-8359 |
language | English |
last_indexed | 2024-03-09T08:08:55Z |
publishDate | 2019-04-01 |
publisher | PeerJ Inc. |
record_format | Article |
series | PeerJ |
spelling | doaj.art-ba9a9355e95e4b6ebe9cbfbb801f66b02023-12-02T23:35:09ZengPeerJ Inc.PeerJ2167-83592019-04-017e633510.7717/peerj.6335Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networksLilija Aprupe0Geert Litjens1Titus J. Brinker2Jeroen van der Laak3Niels Grabe4Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BioQuant, Heidelberg University, Heidelberg, GermanyDepartment of Pathology, Radboud University Medical Center, Nijmegen, The NetherlandsDepartment of Dermatology and National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, GermanyDepartment of Pathology, Radboud University Medical Center, Nijmegen, The NetherlandsHamamatsu Tissue Imaging and Analysis (TIGA) Center, BioQuant, Heidelberg University, Heidelberg, GermanyRecent 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.https://peerj.com/articles/6335.pdfLung cancerImmune cellsDeep learningCancer micro-environmentBiomarker quantification |
spellingShingle | Lilija Aprupe Geert Litjens Titus J. Brinker Jeroen van der Laak Niels Grabe Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks PeerJ Lung cancer Immune cells Deep learning Cancer micro-environment Biomarker quantification |
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 | Lung cancer Immune cells Deep learning Cancer micro-environment Biomarker quantification |
url | https://peerj.com/articles/6335.pdf |
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