Cell segmentation assigns image pixels or voxels to individual cells or their regions. It can distinguish foreground from background, separate touching cells, and label each object for later measurements. For example, a fluorescent nuclear image can support counting nuclei, but nuclear boundaries need not coincide with whole-cell boundaries. Thresholding, geometric models and learned methods make different assumptions about contrast and shape. Errors such as merging two cells or splitting one cell can bias counts and size distributions, so evaluation must match the biological quantity being measured.
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