Interact with the image to see before and after.
Adjust the slider to view the 'before and after' comparison.
Automated counting of nuclei is crucial for many applications and further downstream analyses. This solution is based on a pre-trained deep-learning model, automatically segmenting, separating, and counting nuclei based on any fluorescent nuclear marker such as DAPI in one or more microscopy images. It supports time series images as well as multi-well measurements. The output is a matrix that shows the number of nuclei per image in each well per time point (if applicable). The respective deep-learning model is trained on datasets from multiple microscopes with different resolutions & magnifications.
Figure 1: A heat map representation is generated, indicating the number of nuclei per image in each well across a 96-well plate (red: high, blue: low).