I would like to automatically detect nucleoli in DIC/brightfield images of zygotes. I tried some traditional image processing pipelines but failed so I would like to use deep-learning. In principle I do not need an exact segmentation of the nucleoli and it is enough to identify the centroids.
The object I am interested are in magenta.
However, as mentioned in the forum stardist may be an overkill to just estimate centroids. Furthermore, clicking on centroids is much faster than painting larger areas.
Does anyone of you (e.g. @uschmidt83, @haesleinhuepf, @fjug, @oburri ) have a suggestion for deep-learning workflows to identify centroids/points in an image? This should be easier then segmentation and with a much faster training.