Organotchi: an open-source tool for the automated segmentation, morphological characterization, and longitudinal tracking of organoids

Neural organoids are three-dimensional stem cell-derived models widely used to study brain development and model disease. Brightfield imaging offers a non-invasive readout of their growth and morphology, and recent advances have made automated organoid segmentation from such images increasingly attainable. Yet existing tools largely leave morphological characterization, quality assessment, and comparisons between conditions to manual or ad hoc analysis. Here we present Organotchi, an open-source tool that integrates automated segmentation with longitudinal morphological analysis of neural organoids. Organotchi quantifies ten morphological features, including area, perimeter, and eccentricity, and tracks cystic structures over time, reports variability within and between batches, and flags outlier organoids and segmentation failures, supporting objective organoid characterization and enhancing downstream analysis. As a proof of concept, we apply Organotchi to disease modelling, pharmacological perturbation, and protocol optimization in neural organoids. One use case assesses drug response in breast cancer spheroids, demonstrating its use beyond its development domain.