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Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations

Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image seq...

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Autores principales: Ker, Dai Fei Elmer, Eom, Sungeun, Sanami, Sho, Bise, Ryoma, Pascale, Corinne, Yin, Zhaozheng, Huh, Seung-il, Osuna-Highley, Elvira, Junkers, Silvina N., Helfrich, Casey J., Liang, Peter Yongwen, Pan, Jiyan, Jeong, Soojin, Kang, Steven S., Liu, Jinyu, Nicholson, Ritchie, Sandbothe, Michael F., Van, Phu T., Liu, Anan, Chen, Mei, Kanade, Takeo, Weiss, Lee E., Campbell, Phil G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233481/
https://www.ncbi.nlm.nih.gov/pubmed/30422120
http://dx.doi.org/10.1038/sdata.2018.237
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author Ker, Dai Fei Elmer
Eom, Sungeun
Sanami, Sho
Bise, Ryoma
Pascale, Corinne
Yin, Zhaozheng
Huh, Seung-il
Osuna-Highley, Elvira
Junkers, Silvina N.
Helfrich, Casey J.
Liang, Peter Yongwen
Pan, Jiyan
Jeong, Soojin
Kang, Steven S.
Liu, Jinyu
Nicholson, Ritchie
Sandbothe, Michael F.
Van, Phu T.
Liu, Anan
Chen, Mei
Kanade, Takeo
Weiss, Lee E.
Campbell, Phil G.
author_facet Ker, Dai Fei Elmer
Eom, Sungeun
Sanami, Sho
Bise, Ryoma
Pascale, Corinne
Yin, Zhaozheng
Huh, Seung-il
Osuna-Highley, Elvira
Junkers, Silvina N.
Helfrich, Casey J.
Liang, Peter Yongwen
Pan, Jiyan
Jeong, Soojin
Kang, Steven S.
Liu, Jinyu
Nicholson, Ritchie
Sandbothe, Michael F.
Van, Phu T.
Liu, Anan
Chen, Mei
Kanade, Takeo
Weiss, Lee E.
Campbell, Phil G.
author_sort Ker, Dai Fei Elmer
collection PubMed
description Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image sequences, each spanning approximately 3.5 days, were generated with accompanying ground truths for C2C12 myoblast cells cultured under 4 different media conditions, including with fibroblast growth factor 2 (FGF2), bone morphogenetic protein 2 (BMP2), FGF2 + BMP2, and control (no growth factor). The ground truths generated contain information for tracking at least 3 parent cells and their descendants within these datasets and were validated using a two-tier system of manual curation. This comprehensive, validated dataset will be useful in advancing the development of computer-aided cell tracking algorithms and function as a benchmark, providing an invaluable opportunity to deepen our understanding of individual and population-based cell dynamics for biomedical research.
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spelling pubmed-62334812018-11-14 Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations Ker, Dai Fei Elmer Eom, Sungeun Sanami, Sho Bise, Ryoma Pascale, Corinne Yin, Zhaozheng Huh, Seung-il Osuna-Highley, Elvira Junkers, Silvina N. Helfrich, Casey J. Liang, Peter Yongwen Pan, Jiyan Jeong, Soojin Kang, Steven S. Liu, Jinyu Nicholson, Ritchie Sandbothe, Michael F. Van, Phu T. Liu, Anan Chen, Mei Kanade, Takeo Weiss, Lee E. Campbell, Phil G. Sci Data Data Descriptor Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image sequences, each spanning approximately 3.5 days, were generated with accompanying ground truths for C2C12 myoblast cells cultured under 4 different media conditions, including with fibroblast growth factor 2 (FGF2), bone morphogenetic protein 2 (BMP2), FGF2 + BMP2, and control (no growth factor). The ground truths generated contain information for tracking at least 3 parent cells and their descendants within these datasets and were validated using a two-tier system of manual curation. This comprehensive, validated dataset will be useful in advancing the development of computer-aided cell tracking algorithms and function as a benchmark, providing an invaluable opportunity to deepen our understanding of individual and population-based cell dynamics for biomedical research. Nature Publishing Group 2018-11-13 /pmc/articles/PMC6233481/ /pubmed/30422120 http://dx.doi.org/10.1038/sdata.2018.237 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Ker, Dai Fei Elmer
Eom, Sungeun
Sanami, Sho
Bise, Ryoma
Pascale, Corinne
Yin, Zhaozheng
Huh, Seung-il
Osuna-Highley, Elvira
Junkers, Silvina N.
Helfrich, Casey J.
Liang, Peter Yongwen
Pan, Jiyan
Jeong, Soojin
Kang, Steven S.
Liu, Jinyu
Nicholson, Ritchie
Sandbothe, Michael F.
Van, Phu T.
Liu, Anan
Chen, Mei
Kanade, Takeo
Weiss, Lee E.
Campbell, Phil G.
Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
title Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
title_full Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
title_fullStr Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
title_full_unstemmed Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
title_short Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
title_sort phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233481/
https://www.ncbi.nlm.nih.gov/pubmed/30422120
http://dx.doi.org/10.1038/sdata.2018.237
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