This paper has been published in Scientific Reports (2025). It presents an automated pipeline that translates MR images to CT-like contrast and applies super-resolution to enable accurate, unsupervised skull segmentation, dramatically speeding preparation of 3D skull geometry for implant design. The method reduces reliance on manual labels and improves robustness on clinical data, helping DeepImplant extract bone geometry faster and more reliably.