Organoid-Grader is an automated quality-control tool that classifies brightfield brain organoid images as pass or fail based on morphological features such as tissue uniformity, necrotic core, Feret diameter, and cyst formation. It combines literature-informed rule-based grading with a Random Forest classifier trained on the Schroter et al. dataset (~1,400 images), so labs can gate organoids before costly downstream assays. A future iteration would add non-morphological checks—such as DNA methylation clocks—to confirm that donor cell lines are epigenetically reset before differentiation, strengthening confidence in neurodegenerative and neurodevelopmental disease models.
