Automated Implant Resizing for Single-Stage Cranioplasty

Shuya Liu, Wei Lun Huang, Chad Gordon, Mehran Armand

Research output: Contribution to journalArticlepeer-review


Patient-specific customized cranial implants (CCIs) are designed to fill the bony voids in the cranial and craniofacial skeleton. The current clinical approach during single-stage cranioplasty involves a surgeon modifying an oversized CCI to fit a patient's skull defect. The manual process, however, can be imprecise and time-consuming. This article presents an automated surgical workflow with a robotic workstation for intraoperative CCI modification that provides higher resizing accuracy compared to the manual approach. We proposed a 2-scan method for intraoperative patient-to-CT registration using reattachable fiducial markers to address the registration issue caused by the clinical draping requirement. First, the draped defected skull was 3D scanned and registered to the CT space using our proposed 2-scan registration method. Next, our algorithm generates a robot cutting toolpath based on the 3D defect model. The robot then performs automatic 3D scanning to localize the implant and resizes the implant to match the cranial defect. We evaluated the implant resizing accuracy of the proposed paradigm against the resizing accuracy of the manual approach by an expert surgeon on two plastic skulls and two cadavers. The evaluation results showed that our system was able to decrease the bone gap distance by more than 60% and 30% on plastic skulls and cadavers respectively compared to the manual approach, indicating lower risk of post-surgical complication and better aesthetic restoration.

Original languageEnglish (US)
Article number9476902
Pages (from-to)6624-6631
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number4
StatePublished - Oct 2021


  • 3D scanning
  • Medical robots and systems
  • automation
  • surgical robotics: planning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence


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