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|a 10.2144/btn-2018-0072
|2 doi
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|a eng
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1 |
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|a Tiong, Kai Hung
|e verfasserin
|4 aut
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| 245 |
1 |
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|a QuickCount®
|b a novel automated software for rapid cell detection and quantification
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|c 2018
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|a Text
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|a Date Completed 31.07.2019
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|a Date Revised 31.07.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a 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
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|a accurate
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|a automation
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|a cell count
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|a cell quantification
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|a scalable
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|a time-efficient
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|a user-friendly
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1 |
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|a Chang, Jit Kang
|e verfasserin
|4 aut
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|a Pathmanathan, Dharini
|e verfasserin
|4 aut
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1 |
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|a Hidayatullah Fadlullah, Muhammad Zaki
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| 700 |
1 |
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|4 aut
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1 |
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|e verfasserin
|4 aut
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| 700 |
1 |
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|a Abdul Rahman, Zainal Ariff
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Beh, Kheng Ling
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Cheong, Sok Ching
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t BioTechniques
|d 1988
|g 65(2018), 6 vom: 26. Dez., Seite 322-330
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|x 1940-9818
|7 nnns
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|g volume:65
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