Towards the Automatization of Cranial Implant Design for 3D Printing

Fast and fully automatic design of 3-D printed patient-specific cranial implant is highly desired in cranioplasty. To this end, various deep learning-based approaches are investigated. To facilitate supervised training, a database containing 200 high-resolution healthy CT skulls acquired in clinical routine is constructed. Due to the unavailability of large number of defected skulls from clinic, artificial defects are introduced to simulate that caused in a real cranial surgery.