Counting Unstained, Confluent Cells by Modified Bright-Field Microscopy

Abstract

We present a very simple procedure yielding high-contrast images of adherent, confluent cells such as human neuroblastoma (SH-EP) cells by ordinary bright-field microscopy. Cells are illuminated through a color filter and a pinhole aperture placed between the condenser and the cell culture surface. Refraction by each cell body generates a sharp, bright spot when the image is defocused. The technique allows robust, automatic cell counting from a single bright-field image in a wide range of focal positions; it does this via free, readily available image-analysis tools. Contrast may be enhanced by swelling cell bodies by brief incubation in PBS. The procedure was benchmarked against manual counting and automated counting of fluorescently labeled cell nuclei.. Counts from day-old and freshly seeded plates were compared in a range of densities, from sparse to densely overgrown. On average bright-field images produced the same counts as fluorescent images, with less than 5% error. This method will allow routine cell counting using a plain bright-field microscope, absent cell-line modification or cell staining.

Acetyl-CoA carboxylase rewires cancer metabolism to allow cancer cells to survive inhibition of the Warburg effect by cetuximab

“…Five different areas were then randomly selected and imaged under a fluorescence microscope. The imaging data were analyzed using the ImageJ software program, and cell survival proportions were calculated by dividing the number of surviving cells at various time points after the switch to low glucose medium by the number of surviving cells before the switch [22-26]. …”

Investigation of autofocus algorithms for brightfield microscopy of unstained cells

“…3(a), all of the metrics provide reasonable performance for the absorbent object except for metrics (14) and (15). The result of metric (14) is a straight line because the minimum value of the images is always zero in this particular case leading to the constant contrast((maxima − 0)/(maxima + 0) = 1).…”

“…For an in-focus image containing a high content of image detail we can expect that the contrast will be relatively large, while for a defocused monotone image we can expect it to be relatively small. 15. Histogram Entropy:…”

“…We can identify that metrics (1), (3), (4), (6), (12) and (14), all have a local minimum around the correct focal position but are not well pronounced. However, six of the metrics: (8), (9), (10), (11), (13) and (15) all provide the smooth and distinctive global minimum value corresponding to the most in-focus image. Among those six metrics, four of them, (8), (9), (10) and (11) are all based on variance and they all display similar characteristics.…”

“…5,8 In the past decade there has been increasing attention on image processing algorithms for bright field microscopy in order to enhance the overall functionality of the technique, particularly for imaging transparent unstained cells. [9][10][11][12][13][14][15][16] Many of these papers discuss algorithms that have been shown to successfully calculate the cell boundary and the cell nucleus for transparent unstained cells that have been recorded using brightfield microscopy. In particular level set contouring has been shown to successfully segment unstained cells.…”