An automated cell viability quantification method for low-resolution confocal images of closely packed cells based on...

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.