A machine learning-based approach to segment curved fibers in a binarized µCT image is presented. A neural network has been trained to label the center curve of each fiber using synthetic training data generated with the GeoDict software. The analysis of these centerlines provides an analytical representation of individual fibers, allowing for analysis of diameter, orientation distribution, curliness, and more.