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Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy
Understanding cells as integrated systems is a challenge central to modern biology. The different microscopy approaches used to probe biological organization each present limitations, ultimately restricting insight into unified cellular processes. Fluorescence microscopy can resolve subcellular stru...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6212323/ https://www.ncbi.nlm.nih.gov/pubmed/30224672 http://dx.doi.org/10.1038/s41592-018-0111-2 |
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author | Ounkomol, Chawin Seshamani, Sharmishtaa Maleckar, Mary M. Collman, Forrest Johnson, Gregory R. |
author_facet | Ounkomol, Chawin Seshamani, Sharmishtaa Maleckar, Mary M. Collman, Forrest Johnson, Gregory R. |
author_sort | Ounkomol, Chawin |
collection | PubMed |
description | Understanding cells as integrated systems is a challenge central to modern biology. The different microscopy approaches used to probe biological organization each present limitations, ultimately restricting insight into unified cellular processes. Fluorescence microscopy can resolve subcellular structure in living cells, but is expensive, slow, and toxic. Here, we present a label-free method for predicting 3D fluorescence directly from transmitted light images and demonstrate its use to generate multi-structure, integrated images. |
format | Online Article Text |
id | pubmed-6212323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-62123232019-03-17 Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy Ounkomol, Chawin Seshamani, Sharmishtaa Maleckar, Mary M. Collman, Forrest Johnson, Gregory R. Nat Methods Article Understanding cells as integrated systems is a challenge central to modern biology. The different microscopy approaches used to probe biological organization each present limitations, ultimately restricting insight into unified cellular processes. Fluorescence microscopy can resolve subcellular structure in living cells, but is expensive, slow, and toxic. Here, we present a label-free method for predicting 3D fluorescence directly from transmitted light images and demonstrate its use to generate multi-structure, integrated images. 2018-09-17 2018-11 /pmc/articles/PMC6212323/ /pubmed/30224672 http://dx.doi.org/10.1038/s41592-018-0111-2 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Ounkomol, Chawin Seshamani, Sharmishtaa Maleckar, Mary M. Collman, Forrest Johnson, Gregory R. Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy |
title | Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy |
title_full | Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy |
title_fullStr | Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy |
title_full_unstemmed | Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy |
title_short | Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy |
title_sort | label-free prediction of three-dimensional fluorescence images from transmitted light microscopy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6212323/ https://www.ncbi.nlm.nih.gov/pubmed/30224672 http://dx.doi.org/10.1038/s41592-018-0111-2 |
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