Mathematics and System Engineering Faculty Publications
Document Type
Article
Publication Title
BioTechniques
Abstract
Microscale technologies have emerged as a powerful tool for studying and manipulating biological systems and miniaturizing experiments. However, the lack of software complementing these techniques has made it difficult to apply them for many high-throughput experiments. This work establishes Arraycount, an approach to automatically count cells in microwell arrays. The procedure consists of fluorescent microscope imaging of cells that are seeded in microwells of a microarray system and then analyzing images via computer to recognize the array and count cells inside each microwell. To start counting, green and red fluorescent images (representing live and dead cells, respectively) are extracted from the original image and processed separately. A template-matching algorithm is proposed in which pre-defined well and cell templates are matched against the red and green images to locate microwells and cells. Subsequently, local maxima in the correlation maps are determined and local maxima maps are thresholded. At the end, the software records the cell counts for each detected microwell on the original image in high-throughput. The automated counting was shown to be accurate compared with manual counting, with a difference of ∼1–2 cells per microwell: based on cell concentration, the absolute difference between manual and automatic counting measurements was 2.5–13%.
DOI
10.2144/000113202
Publication Date
2009
Recommended Citation
Kachouie, Nezamoddin N.; Lifeng, Kang; and Ali, Khademhosseini, "Arraycount, an algorithm for automatic cell counting in microwell arrays" (2009). Mathematics and System Engineering Faculty Publications. 190.
https://repository.fit.edu/math_faculty/190