Spatially-smoothed quantification improves cell typing in imaging mass cytometry datasets.

ABSTRACT: Accurate cell type annotation in imaging mass cytometry (IMC) and related technologies critically depends on preprocessing steps such as normalization, segmentation, and marker aggregation. More distinct separation between negative and positive signals enables more precise cell boundary inference and more robust marker assignment to single cells. However, inherent limitations in spatial resolution and uncertain cell boundaries can lead to spillover, where signal leaks from one cell to a neighboring cell, distorting marker intensities and leading to incorrect cell type annotation. To address these challenges, we first systematically investigated the impact of spatial resolution and segmentation variability on per-cell marker aggregation using simulated IMC datasets, establishing upper limit

SUBMITTER: Gerber R 

PROVIDER: S-EPMC12724609 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature