Tracking immune cells is hard because microscope images can be low-resolution and cells move in unpredictable, jittery paths. Standard software often cannot tell similar-looking cells apart when they are packed together. UCF’s open-source CancerCellTracker and machine-learning tools like TLCellClassifier help scientists follow thousands of individual cells at once.