For the study of glass fiber-reinforced polymers (GFRP),μCT is the method of choice. ObtainingGFRP parameters from aμCT scan is difficult, due to the presence of noise and artifacts. We propose a methodto improve GFRP image quality using a recently introduced deep neural network. We describe the network’ssetup and the data generation and show how the trained network improves the reconstruction.