An automated cell viability quantification method for low‐resolution confocal images of closely packed cells based on a modified gradient flow tracking algorithm

Fluorescent‐based live/dead labelling combined with fluorescent microscopy is one of the widely used and reliable methods for assessment of cell viability. This method is, however, not quantitative. Many image‐processing methods have been proposed for cell quantification in an image. Among all these methods, several of them are capable of quantifying the number of cells in high‐resolution images with closely packed cells. However, no method has addressed the quantification of the number of cells in low‐resolution images containing closely packed cells with variable sizes. This paper presents a novel method for automatic quantification of live/dead cells in 2D fluorescent low‐resolution images containing closely packed cells with variable sizes using a mean shift‐based gradient flow tracking. Accuracy and performance of the method was tested on growth plate confocal images. Experimental results show that our algorithm has a better performance in comparison to other methods used in similar detection conditions.