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Pipeline for illumination correction of images for high-throughput microscopy
The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BlackWell Publishing Ltd
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359755/ https://www.ncbi.nlm.nih.gov/pubmed/25228240 http://dx.doi.org/10.1111/jmi.12178 |
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author | Singh, S Bray, M-A Jones, TR Carpenter, AE |
author_facet | Singh, S Bray, M-A Jones, TR Carpenter, AE |
author_sort | Singh, S |
collection | PubMed |
description | The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z′-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. |
format | Online Article Text |
id | pubmed-4359755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BlackWell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-43597552015-03-19 Pipeline for illumination correction of images for high-throughput microscopy Singh, S Bray, M-A Jones, TR Carpenter, AE J Microsc Original Articles The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z′-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. BlackWell Publishing Ltd 2014-12 2014-09-16 /pmc/articles/PMC4359755/ /pubmed/25228240 http://dx.doi.org/10.1111/jmi.12178 Text en © 2014 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Singh, S Bray, M-A Jones, TR Carpenter, AE Pipeline for illumination correction of images for high-throughput microscopy |
title | Pipeline for illumination correction of images for high-throughput microscopy |
title_full | Pipeline for illumination correction of images for high-throughput microscopy |
title_fullStr | Pipeline for illumination correction of images for high-throughput microscopy |
title_full_unstemmed | Pipeline for illumination correction of images for high-throughput microscopy |
title_short | Pipeline for illumination correction of images for high-throughput microscopy |
title_sort | pipeline for illumination correction of images for high-throughput microscopy |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359755/ https://www.ncbi.nlm.nih.gov/pubmed/25228240 http://dx.doi.org/10.1111/jmi.12178 |
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