People saying get more than 100 images are right (all else being equal, yes, get more images!) but you likely can make good progress without as many images for your problem with clever augmentation and a smaller network.

Here’s why:

1. You only have to detect cavities. It’s not some 1,000-class semantic segmentation problem.

2. You should be working with single channel grayscale images, and not pixels that naturally come in 3-channel RGB color.

3. This is X-ray data just of teeth, so you don’t have nearly the amount of complex fine-detailed textures and patterns (with colors) that are exhibited in more general RGB optical datasets of all sorts of objects and environments.

Of course for a real operational system that you will use in commercial products you will need to get far more than 100 images. However, for a simple research problem or prototype demo, you can likely show good results and feasibility (without overfitting, yes) on your dataset with a smaller net and clever augmentation.