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Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search
Cell proliferation is critical to the outgrowth of biological structures including the face and limbs. This cellular process has traditionally been studied via sequential histological sampling of these tissues. The length and tedium of traditional sampling is a major impediment to analyzing the larg...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3124674/ https://www.ncbi.nlm.nih.gov/pubmed/21747822 http://dx.doi.org/10.1155/2011/874702 |
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author | Meruvia-Pastor, Oscar E. Soh, Jung Schmidt, Eric J. Boughner, Julia C. Xiao, Mei Jamniczky, Heather A. Hallgrímsson, Benedikt Sensen, Christoph W. |
author_facet | Meruvia-Pastor, Oscar E. Soh, Jung Schmidt, Eric J. Boughner, Julia C. Xiao, Mei Jamniczky, Heather A. Hallgrímsson, Benedikt Sensen, Christoph W. |
author_sort | Meruvia-Pastor, Oscar E. |
collection | PubMed |
description | Cell proliferation is critical to the outgrowth of biological structures including the face and limbs. This cellular process has traditionally been studied via sequential histological sampling of these tissues. The length and tedium of traditional sampling is a major impediment to analyzing the large datasets required to accurately model cellular processes. Computerized cell localization and quantification is critical for high-throughput morphometric analysis of developing embryonic tissues. We have developed the Incremental Cell Search (ICS), a novel software tool that expedites the analysis of relationships between morphological outgrowth and cell proliferation in embryonic tissues. Based on an estimated average cell size and stain color, ICS rapidly indicates the approximate location and amount of cells in histological images of labeled embryonic tissue and provides estimates of cell counts in regions with saturated fluorescence and blurred cell boundaries. This capacity opens the door to high-throughput 3D and 4D quantitative analyses of developmental patterns. |
format | Online Article Text |
id | pubmed-3124674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-31246742011-07-11 Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search Meruvia-Pastor, Oscar E. Soh, Jung Schmidt, Eric J. Boughner, Julia C. Xiao, Mei Jamniczky, Heather A. Hallgrímsson, Benedikt Sensen, Christoph W. Int J Biomed Imaging Research Article Cell proliferation is critical to the outgrowth of biological structures including the face and limbs. This cellular process has traditionally been studied via sequential histological sampling of these tissues. The length and tedium of traditional sampling is a major impediment to analyzing the large datasets required to accurately model cellular processes. Computerized cell localization and quantification is critical for high-throughput morphometric analysis of developing embryonic tissues. We have developed the Incremental Cell Search (ICS), a novel software tool that expedites the analysis of relationships between morphological outgrowth and cell proliferation in embryonic tissues. Based on an estimated average cell size and stain color, ICS rapidly indicates the approximate location and amount of cells in histological images of labeled embryonic tissue and provides estimates of cell counts in regions with saturated fluorescence and blurred cell boundaries. This capacity opens the door to high-throughput 3D and 4D quantitative analyses of developmental patterns. Hindawi Publishing Corporation 2011 2011-05-24 /pmc/articles/PMC3124674/ /pubmed/21747822 http://dx.doi.org/10.1155/2011/874702 Text en Copyright © 2011 Oscar E. Meruvia-Pastor et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Meruvia-Pastor, Oscar E. Soh, Jung Schmidt, Eric J. Boughner, Julia C. Xiao, Mei Jamniczky, Heather A. Hallgrímsson, Benedikt Sensen, Christoph W. Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search |
title | Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search |
title_full | Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search |
title_fullStr | Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search |
title_full_unstemmed | Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search |
title_short | Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search |
title_sort | estimating cell count and distribution in labeled histological samples using incremental cell search |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3124674/ https://www.ncbi.nlm.nih.gov/pubmed/21747822 http://dx.doi.org/10.1155/2011/874702 |
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