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Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms
The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisit...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737281/ https://www.ncbi.nlm.nih.gov/pubmed/29048559 http://dx.doi.org/10.1093/gigascience/gix092 |
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author | Perez-Sanz, Fernando Navarro, Pedro J Egea-Cortines, Marcos |
author_facet | Perez-Sanz, Fernando Navarro, Pedro J Egea-Cortines, Marcos |
author_sort | Perez-Sanz, Fernando |
collection | PubMed |
description | The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. |
format | Online Article Text |
id | pubmed-5737281 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57372812018-01-08 Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms Perez-Sanz, Fernando Navarro, Pedro J Egea-Cortines, Marcos Gigascience Review The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. Oxford University Press 2017-10-03 /pmc/articles/PMC5737281/ /pubmed/29048559 http://dx.doi.org/10.1093/gigascience/gix092 Text en © The Author 2017. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Perez-Sanz, Fernando Navarro, Pedro J Egea-Cortines, Marcos Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms |
title | Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms |
title_full | Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms |
title_fullStr | Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms |
title_full_unstemmed | Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms |
title_short | Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms |
title_sort | plant phenomics: an overview of image acquisition technologies and image data analysis algorithms |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737281/ https://www.ncbi.nlm.nih.gov/pubmed/29048559 http://dx.doi.org/10.1093/gigascience/gix092 |
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