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Segmentation was done using a watershed algorithm [36] to identify the dominant peak in the surface.
First, the visible sky is roughly segmented from the textureless area of the captured image using a watershed algorithm.
The detection algorithm follows a pattern recognition methodology steps as follows: Step 1: Segmentation: different regions are found and isolated from the rest of the X-ray image using a watershed algorithm and morphological operations (erosion and dilation).
Finally, the nuclei are separated using a Watershed algorithm [ 44].
Briefly, cells were identified from phase images using a watershed algorithm.
Candidate foci were identified globally using a watershed algorithm, then assigned to cells whose masks overlapped the focus position.
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The crown polygon layer was created using a watershed transformation algorithm applied to the CHM that segmented individual tree crowns that are isolated in height from adjacent regions.
Individual fluorescent foci were isolated using a watershed-based segmentation algorithm and fit using a Gaussian point-spread function.
Subsequently, it removed background noise by using an adaptive median filter that estimated the noise level, and enhanced the location of all labelled RyRs with a 2D Gaussian filter with a standard deviation of 0.5 µm followed by segmentation using a multilevel watershed algorithm.
Using a variation of a watershed algorithm, we segmented individual cells, assigning a unique ID to each epithelial cell.
Stitched images were then loaded in Packing Analyzer v8.5 (PA8.5) for cell edge detection by using a seeded-watershed algorithm.
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