Chapter title |
Cell Population Tracking and Lineage Construction with Spatiotemporal Context
|
---|---|
Chapter number | 36 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007
|
Published in |
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, October 2007
|
DOI | 10.1007/978-3-540-75759-7_36 |
Pubmed ID | |
Book ISBNs |
978-3-54-075758-0, 978-3-54-075759-7
|
Authors |
Li, Kang, Chen, Mei, Kanade, Takeo, Kang Li, Mei Chen, Takeo Kanade |
Abstract |
Automated visual-tracking of cell populations in vitro using phase contrast time-lapse microscopy is vital for quantitative, systematic and high-throughput measurements of cell behaviors. These measurements include the spatiotemporal quantification of migration, mitosis, apoptosis, and cell lineage. This paper presents an automated cell tracking system that can simultaneously track and analyze thousands of cells. The system performs tracking by cycling through frame-by-frame track compilation and spatiotemporal track linking, combining the power of two tracking paradigms. We applied the system to a range of cell populations including adult stem cells. The system achieved tracking accuracies in the range of 83.8%-92.5%, outperforming previous work by up to 8%. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 3 | 5% |
United States | 2 | 3% |
Netherlands | 1 | 2% |
Japan | 1 | 2% |
Belgium | 1 | 2% |
Unknown | 53 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 17 | 28% |
Researcher | 14 | 23% |
Student > Master | 7 | 11% |
Professor | 4 | 7% |
Student > Doctoral Student | 3 | 5% |
Other | 6 | 10% |
Unknown | 10 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 20 | 33% |
Agricultural and Biological Sciences | 13 | 21% |
Engineering | 7 | 11% |
Physics and Astronomy | 4 | 7% |
Mathematics | 2 | 3% |
Other | 4 | 7% |
Unknown | 11 | 18% |