QuickCount ® : A novel automated software for rapid cell detection and quantification

Tiong, Kai Hung and Chang, Jit Kang and Pathmanathan, Dharini and Fadlullah, Muhammad Zaki Hidayatullah and Yee, Pei San and Liew, Chee Sun and Rahman, Zainal Ariff Abdul and Beh, Kheng Ling and Cheong, Sok Ching (2018) QuickCount ® : A novel automated software for rapid cell detection and quantification. BioTechniques, 65 (6). pp. 322-330. ISSN 0736-6205

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Official URL: https://doi.org/10.2144/btn-2018-0072

Abstract

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 ImageJ auto , CellProfiler and CellC and the precision of QC, ImageJ auto , 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.

Item Type: Article
Uncontrolled Keywords: accurate; automation; cell count; cell quantification; scalable; time-efficient; user-friendly
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RK Dentistry
Divisions: Faculty of Computer Science & Information Technology
Faculty of Dentistry
Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 25 Feb 2019 02:45
Last Modified: 25 Feb 2019 02:45
URI: http://eprints.um.edu.my/id/eprint/20464

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