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

Authors :
Dai Fei Elmer Ker
Jiyan Pan
Casey J. Helfrich
Phil G. Campbell
Jinyu Liu
Ryoma Bise
Zhaozheng Yin
Ritchie Nicholson
Peter Liang
Sho Sanami
Michael F. Sandbothe
Silvina N. Junkers
An-An Liu
Sungeun Eom
Phu T. Van
Soojin Jeong
Steven S. Kang
Seungil Huh
Takeo Kanade
Lee E. Weiss
Elvira Osuna-Highley
Mei Chen
Corinne Pascale
Source :
Scientific Data
Publication Year :
2018
Publisher :
Springer Science and Business Media LLC, 2018.

Abstract

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. Machine-accessible metadata file describing the reported data (ISA-Tab format)

Details

ISSN :
20524463
Volume :
5
Database :
OpenAIRE
Journal :
Scientific Data
Accession number :
edsair.doi.dedup.....65cdb2aa95f44a6ea3e71aa567c9ab80