The researchers wanted to figure out how many training examples and what kind of artificial data could help a computer program accurately segment brain ventricles in preterm babies using ultrasound images. They found that with just 9 training examples, the program could do a good job. They also discovered that flipping images horizontally improved the program's accuracy, but other types of data augmentation didn't make a big difference.