iOrganoAssay to Connect Microscopy Images to Organoid Assays for Long-Term Monitoring

We present the use of iOrganoAssay (images of Organoid Assay) to connect microscopy images with organoid assessment assays such as live–dead, immunocytochemistry, and drug treatment assays. The iOrganoAssay consists of an R script-based application (App) interface and datasets encompassing (1) microscopy images, (2) segmentation results, (3) morphometric data, (4) a metadata file, and (5) a validation dataset. The microscopy image collection includes 234 large-area images of intestinal organoids cultured in Matrigel dome region (~3 mm), acquired using an automated stage-equipped microscopy system. Upon treatment with dextran sulfate sodium (DSS), microscopy images of morphological changes in intestinal organoids were captured and quantified. Image segmentation was performed to extract organoid morphological data, including area, perimeter, and circularity. These metrics were plotted to visualize daily variations, enabling systematic tracking of drug-induced morphological changes over time. Statistical comparisons were also provided using violin plots. To evaluate segmentation quality, we established a validation dataset of 28 manually annotated organoids (14 control, 14 DSS-treated) and calculated Dice scores, accuracy (Acc), segmentation error (SegErr), and centroid error (CenErr). This integrated dataset—covering organoid images, segmentation outputs, morphometric data, and validation metrics—provides a resource for organoid image-based studies in morphological monitoring and segmentation validation.