PaperS7555
CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images
CellSeg combines a pretrained nucleus-segmentation model with image scaling, stitching, mask expansion and pixel statistics. Historical benchmark scores and representative tissue examples have different provenance and settings; densely packed tissue remains difficult. A colorectal comparison reuses 140 samples from 35 people and provides author-described gating and correlation. Correlation does not establish exhaustive cell truth or universal clinical accuracy. Source-native metric definitions, count conflicts and caption errors are preserved.
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