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Segmentation of Total Cell Area in Brightfield Microscopy Images
Segmentation is one of the most important steps in microscopy image analysis. Unfortunately, most of the methods use fluorescence images for this task, which is not suitable for analysis that requires a knowledge of area occupied by cells and an experimental design that does not allow necessary labe...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481060/ https://www.ncbi.nlm.nih.gov/pubmed/31164583 http://dx.doi.org/10.3390/mps1040043 |
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author | Čepa, Martin |
author_facet | Čepa, Martin |
author_sort | Čepa, Martin |
collection | PubMed |
description | Segmentation is one of the most important steps in microscopy image analysis. Unfortunately, most of the methods use fluorescence images for this task, which is not suitable for analysis that requires a knowledge of area occupied by cells and an experimental design that does not allow necessary labeling. In this protocol, we present a simple method, based on edge detection and morphological operations, that separates total area occupied by cells from the background using only brightfield channel image. The resulting segmented picture can be further used as a mask for fluorescence quantification and other analyses. The whole procedure is carried out in open source software Fiji. |
format | Online Article Text |
id | pubmed-6481060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64810602019-05-31 Segmentation of Total Cell Area in Brightfield Microscopy Images Čepa, Martin Methods Protoc Protocol Segmentation is one of the most important steps in microscopy image analysis. Unfortunately, most of the methods use fluorescence images for this task, which is not suitable for analysis that requires a knowledge of area occupied by cells and an experimental design that does not allow necessary labeling. In this protocol, we present a simple method, based on edge detection and morphological operations, that separates total area occupied by cells from the background using only brightfield channel image. The resulting segmented picture can be further used as a mask for fluorescence quantification and other analyses. The whole procedure is carried out in open source software Fiji. MDPI 2018-11-19 /pmc/articles/PMC6481060/ /pubmed/31164583 http://dx.doi.org/10.3390/mps1040043 Text en © 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Protocol Čepa, Martin Segmentation of Total Cell Area in Brightfield Microscopy Images |
title | Segmentation of Total Cell Area in Brightfield Microscopy Images |
title_full | Segmentation of Total Cell Area in Brightfield Microscopy Images |
title_fullStr | Segmentation of Total Cell Area in Brightfield Microscopy Images |
title_full_unstemmed | Segmentation of Total Cell Area in Brightfield Microscopy Images |
title_short | Segmentation of Total Cell Area in Brightfield Microscopy Images |
title_sort | segmentation of total cell area in brightfield microscopy images |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481060/ https://www.ncbi.nlm.nih.gov/pubmed/31164583 http://dx.doi.org/10.3390/mps1040043 |
work_keys_str_mv | AT cepamartin segmentationoftotalcellareainbrightfieldmicroscopyimages |