You could try fine tuning an already pre-trained network.
Depending on the amount of your data and its mismatch to the dataset used to pre-train the network, you can decide how many layers to fine tune.
The bigger the mismatch (e.g. pre-trained on “natural” images, your dataset contained medical x-ray images), the more layers I would try to fine tune.
Here 8 you can find a nice transfer learning tutorial.