HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics.

ABSTRACT: High-resolution histology images are indispensable for pathology and increasingly serve as the structural backbone for spatial omics. Yet whole-slide images (WSIs) frequently contain artifacts, acellular voids, and background regions that, when included in computational workflows, introduce noise, degrade model accuracy, and compromise biological interpretation. Existing tools provide only coarse foreground-background separation, leaving a gap in fine-grained quality control (QC). Here we present HistoSweep, a scalable framework that generates morphology-aware tissue masks at cellular resolution. By integrating density filtering, texture descriptors, and adaptive thresholding, HistoSweep systematically removes non-informative tissue regions while preserving biologically meaningful microstr

SUBMITTER: Schroeder A 

PROVIDER: S-EPMC12889531 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature