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IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification
Automated quantitative image analysis is essential for all fields of life science research. Although several software programs and algorithms have been developed for bioimage processing, an advanced knowledge of image processing techniques and high-performance computing resources are required to use...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386377/ https://www.ncbi.nlm.nih.gov/pubmed/30794647 http://dx.doi.org/10.1371/journal.pone.0212619 |
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author | Shimahara, Yuki Sugawara, Ko Kojo, Kei H. Kawai, Hiroki Yoshida, Yuya Hasezawa, Seiichiro Kutsuna, Natsumaro |
author_facet | Shimahara, Yuki Sugawara, Ko Kojo, Kei H. Kawai, Hiroki Yoshida, Yuya Hasezawa, Seiichiro Kutsuna, Natsumaro |
author_sort | Shimahara, Yuki |
collection | PubMed |
description | Automated quantitative image analysis is essential for all fields of life science research. Although several software programs and algorithms have been developed for bioimage processing, an advanced knowledge of image processing techniques and high-performance computing resources are required to use them. Hence, we developed a cloud-based image analysis platform called IMACEL, which comprises morphological analysis and machine learning-based image classification. The unique click-based user interface of IMACEL’s morphological analysis platform enables researchers with limited resources to evaluate particles rapidly and quantitatively without prior knowledge of image processing. Because all the image processing and machine learning algorithms are performed on high-performance virtual machines, users can access the same analytical environment from anywhere. A validation study of the morphological analysis and image classification of IMACEL was performed. The results indicate that this platform is an accessible and potentially powerful tool for the quantitative evaluation of bioimages that will lower the barriers to life science research. |
format | Online Article Text |
id | pubmed-6386377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63863772019-03-09 IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification Shimahara, Yuki Sugawara, Ko Kojo, Kei H. Kawai, Hiroki Yoshida, Yuya Hasezawa, Seiichiro Kutsuna, Natsumaro PLoS One Research Article Automated quantitative image analysis is essential for all fields of life science research. Although several software programs and algorithms have been developed for bioimage processing, an advanced knowledge of image processing techniques and high-performance computing resources are required to use them. Hence, we developed a cloud-based image analysis platform called IMACEL, which comprises morphological analysis and machine learning-based image classification. The unique click-based user interface of IMACEL’s morphological analysis platform enables researchers with limited resources to evaluate particles rapidly and quantitatively without prior knowledge of image processing. Because all the image processing and machine learning algorithms are performed on high-performance virtual machines, users can access the same analytical environment from anywhere. A validation study of the morphological analysis and image classification of IMACEL was performed. The results indicate that this platform is an accessible and potentially powerful tool for the quantitative evaluation of bioimages that will lower the barriers to life science research. Public Library of Science 2019-02-22 /pmc/articles/PMC6386377/ /pubmed/30794647 http://dx.doi.org/10.1371/journal.pone.0212619 Text en © 2019 Shimahara 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, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Shimahara, Yuki Sugawara, Ko Kojo, Kei H. Kawai, Hiroki Yoshida, Yuya Hasezawa, Seiichiro Kutsuna, Natsumaro IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification |
title | IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification |
title_full | IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification |
title_fullStr | IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification |
title_full_unstemmed | IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification |
title_short | IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification |
title_sort | imacel: a cloud-based bioimage analysis platform for morphological analysis and image classification |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386377/ https://www.ncbi.nlm.nih.gov/pubmed/30794647 http://dx.doi.org/10.1371/journal.pone.0212619 |
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