arivis Scientific Image Analysis

Cell Counting

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Cell Counting


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Before and After Analysis

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Solution Description

Counting cells is one of the most important and common applications in biology. At the same time, this is a highly challenging task if the cells are not fluorescently labelled or stained. Therefore, classical image processing methods can often not be used for brightfield images.

‍This solution is based on a pre-trained deep-learning network that detects the cells in one or more bright field microscopy images. Time series images as well as multi-well images are supported. The output is a heatmap that shows the number of cells per image in each well and time point (if applicable). The respective deep-learning network is trained on datasets from multiple microscopes with different resolutions/magnifications.‍

63861162f78b032eaf6ed4b9_Cells-plot (1)

Figure 1: Number of cells are plotted as a heat map, indicating the number of cells per image across a 96-well plate (red: high, blue: low).

Deep learning, arivis Cloud, cells, counting,brightfield, phase contrast