Affiliations 

  • 1 Head & Neck Cancer Research Team, Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
  • 2 Data-Intensive Computing Centre, University of Malaya, Kuala Lumpur, Malaysia
  • 3 Institute of Mathematical Sciences, University of Malaya, Kuala Lumpur, Malaysia
  • 4 Department of Oral & Maxillofacial Clinical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia
  • 5 ViTrox Technologies Sdn. Bhd., Bayan Lepas, Penang, Malaysia
Biotechniques, 2018 12;65(6):322-330.
PMID: 30477327 DOI: 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 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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.