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This thesis investigates simulating X-ray computed tomography with two primary objectives: developing a virtual representation of an X-ray computed tomography scanner and generating labelled synthetic training data for deep learning-based fibre segmentation. A simulation pipeline to generate X-ray projections based on the Beer-Lambert law was developed using the open-source framework gVirtualXray.
