TY - GEN
T1 - A Robotic System for Implant Modification in Single-stage Cranioplasty
AU - Liu, Shuya
AU - Huang, Wei Lun
AU - Gordon, Chad
AU - Armand, Mehran
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Craniomaxillofacial reconstruction with patient-specific customized craniofacial implants (CCIs) is most commonly performed for large-sized skeletal defects. Because the exact size of skull resection may not be known prior to the surgery, in single-stage cranioplasty, an oversized CCI is prefabricated and resized intraoperatively with a manual-cutting process provided by a surgeon. The manual resizing, however, may be inaccurate and significantly add to the operating time. This paper introduces a fast and non-contact approach for intraoperatively determining the exact contour of the skull resection and automatically resizing the implant to fit the resection area. Our approach includes four steps: First, we acquire a patient's defect information using a handheld 3D scanner. Second, the scanned defect is aligned to the CCI by registering the scanned defect to the preoperative CT model. Third, a cutting toolpath is generated from the scanned defect model by extracting the resection contour. Lastly, a cutting robot resizes the oversized CCI to fit the resection area. To evaluate the resizing performance of our method, we generated six different resection shapes for the cutting experiments. We compared the performance of our method to the performance of surgeon's manual resizing and an existing technique that collects the defect contour with an optical tracking system. The results show that our proposed method improves the resizing accuracy by 56% compared to the surgeon's manual modification and 42% compared to the optical tracking method.
AB - Craniomaxillofacial reconstruction with patient-specific customized craniofacial implants (CCIs) is most commonly performed for large-sized skeletal defects. Because the exact size of skull resection may not be known prior to the surgery, in single-stage cranioplasty, an oversized CCI is prefabricated and resized intraoperatively with a manual-cutting process provided by a surgeon. The manual resizing, however, may be inaccurate and significantly add to the operating time. This paper introduces a fast and non-contact approach for intraoperatively determining the exact contour of the skull resection and automatically resizing the implant to fit the resection area. Our approach includes four steps: First, we acquire a patient's defect information using a handheld 3D scanner. Second, the scanned defect is aligned to the CCI by registering the scanned defect to the preoperative CT model. Third, a cutting toolpath is generated from the scanned defect model by extracting the resection contour. Lastly, a cutting robot resizes the oversized CCI to fit the resection area. To evaluate the resizing performance of our method, we generated six different resection shapes for the cutting experiments. We compared the performance of our method to the performance of surgeon's manual resizing and an existing technique that collects the defect contour with an optical tracking system. The results show that our proposed method improves the resizing accuracy by 56% compared to the surgeon's manual modification and 42% compared to the optical tracking method.
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U2 - 10.1109/ICRA48506.2021.9560965
DO - 10.1109/ICRA48506.2021.9560965
M3 - Conference contribution
AN - SCOPUS:85111160131
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 12275
EP - 12281
BT - 2021 IEEE International Conference on Robotics and Automation, ICRA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Y2 - 30 May 2021 through 5 June 2021
ER -