QuickCount®: a novel automated software for rapid cell detection and quantification
| Autor: | Kai Hung Tiong, Jit Kang Chang, Dharini Pathmanathan, Muhammad Zaki Hidayatullah Fadlullah, Pei San Yee, Chee Sun Liew, Zainal Ariff Abdul Rahman, Kheng Ling Beh, Sok Ching Cheong |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | BioTechniques, Vol 65, Iss 6, Pp 322-330 (2018) |
| Druh dokumentu: | article |
| ISSN: | 1940-9818 0736-6205 |
| DOI: | 10.2144/btn-2018-0072 |
| Popis: | We describe a novel automated cell detection and counting software, QuickCount® (QC), designed for rapid quantification of cells. The Bland–Altman plot and intraclass correlation coefficient (ICC) analyses demonstrated strong agreement between cell counts from QC to manual counts (mean and SD: -3.3 ± 4.5; ICC = 0.95). QC has higher recall in comparison to ImageJauto, CellProfiler and CellC and the precision of QC, ImageJauto, CellProfiler and CellC are high and comparable. QC can precisely delineate and count single cells from images of different cell densities with precision and recall above 0.9. QC is unique as it is equipped with real-time preview while optimizing the parameters for accurate cell count and needs minimum hands-on time where hundreds of images can be analyzed automatically in a matter of milliseconds. In conclusion, QC offers a rapid, accurate and versatile solution for large-scale cell quantification and addresses the challenges often faced in cell biology research. |
| Databáze: | Directory of Open Access Journals |
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