FLIMExplorer: interactive GUI for object-based visualization and analysis of fluorescence lifetime images

Fluorescence lifetime imaging microscopy (FLIM) enables non-invasive measurement of cellular metabolism with single-cell and subcellular resolution, providing advantages over traditional population-level metabolic assays. However, current single-cell FLIM analysis workflows typically rely on multiple software tools for lifetime extraction, segmentation, and downstream analysis, often resulting in convoluted workflows and a disconnect between quantitative measurements and image context, limiting transparent quality control. Here, we present FLIMExplorer, an interactive, Python-based tool for downstream single-cell FLIM analysis and visualization. FLIMExplorer links quantitative FLIM endpoints and their underlying image objects, enabling users to explore key FLIM features (NAD(P)H and FAD: τ _m, τ ₁, τ ₂, and α ₁) at the single-cell level, visualize image objects corresponding to individual data points, and perform statistical comparisons across experimental groups within a single graphic user interface app. FLIMExplorer handles inputs of both (1) pixel-level FLIM outputs generated by upstream fitting software and (2) pre-processed, cell-average FLIM datasets. By integrating visualization, quality control, and statistical analysis at the single-cell level within a single platform, FLIMExplorer improves the integration of quantitative results with image context in downstream FLIM analysis.