PixlMap: A generalisable pixel classifier for cellular phenotyping in multiplex immunofluorescence images.

ABSTRACT: Multiplexed methods for the detection of protein expression generate extremely data-rich images of intact tissue sections. These images are invaluable for the quantification and analysis of complex biology and biomarker development. However, their interpretation presents a considerable analytical challenge. Cell segmentation from images is a key bottleneck and a major focus of research activity in artificial intelligence. Most current methods depend initially on the use of a nuclear counterstain to identify nuclear boundaries, which is a relatively straightforward task. The cellular boundary is then assigned either by expansion of the nuclear outline, or by the use of membrane or cytoplasm-specific stains to delineate cell boundaries, or by some combination of the two. The task is critical

SUBMITTER: Baird RL 

PROVIDER: S-EPMC12674528 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature