Cytomove: a browser-local and reviewable workflow for scratch wound healing assay quantification

Abstract

The in vitro scratch wound healing assay is one of the most widely used methods for studying collective cell migration, but converting assay images into reproducible measurements remains a practical bottleneck of manual tracing, local software installation, parameter bookkeeping, and limited visibility into how the wound region was segmented. We present Cytomove, a browser-local software tool for reviewable scratch wound healing assay quantification. Cytomove imports local microscopy images, segments the wound region with an explainable variance-and-threshold pipeline implemented in client-side JavaScript without external image-processing dependencies, displays the segmentation as an inspectable overlay before any number is exported, supports single-image and grouped time-course analysis, and exports wound area, wound area fraction, wound width profile statistics, quality-control labels, and full analysis metadata as CSV, Excel, PNG, and ZIP. All processing runs in the browser or in a desktop package built on the same code; microscopy images never leave the users machine. In a preliminary comparison with the ImageJ/Fiji Wound Healing Size Tool (WHST) across five image sets and 31 paired measurements, Cytomove reproduced wound-area behaviour closely in a clean brightfield comparator sequence (mean absolute percentage error 4.1%, Pearson r = 0.9975) and in a phase-contrast time course approaching closure (median area error 6.6%, r = 0.9984), while surfacing near-closure and real-world acquisition difficulties through overlays and quality-control labels. Informal local testing indicates that typical single-image analysis completes within seconds in a modern browser, with no installation or dependency step. Cytomove lowers installation friction, keeps assay data local, and links every exported number to the segmentation image and parameters that produced it.