Nuclei segmentation in 3D data is challenging because of background intensity, uneven intensity in Z-dimension, noise and simply the amoung of pixels which need to be processed. Real-time experience while configuring a workflow for nuclei segmentation can be achieved when utilizing classical methods such as filtering, thresholding and watershed techniques. It is recommended to utilize modern GDDR6-based GPU hardware for 3D segmentation.
Open your data set. Start the CLIJx-Assistant and follow such a workflows:
After assembling your workflow, put these operations next to each other, change the parameters.
Download video [Image data source: Daniela Vorkel, Myers lab, CSBD / MPI CBG]
There are many ways for detecting nuclei and extending their size, e.g. to study neighborhood relationships.
Download video [Image data source: Daniela Vorkel, Myers lab, CSBD / MPI CBG]
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