
Proceedings Paper
Calibration of a hand-held stereovision system for image-guided spinal surgeryFormat | Member Price | Non-Member Price |
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Paper Abstract
The accuracy of image guidance in spinal surgery can be compromised by intervertebral motion between preoperative supine CT images and intraoperative prone positioning. Patient registration and image updating approaches have been developed to register CT images with intraoperative spine and compensate for posture and alignment changes. We have developed a hand-held stereovision (HHS) system to acquire intraoperative profiles of the exposed spine and facilitate image registration and surgical navigation during open spinal surgery. First, we calibrated the stereo parameters using a checkerboard pattern, and the mean reprojection error was 0.33 pixel using 42 image pairs. Second, we attached an active tracker to the HHS device to track its location using a commercial navigation system. We performed spatial calibration to find the transformation between camera space and tracker space, and the error was 0.73 ± 0.39 mm. Finally, we evaluated the accuracy of the HHS using an ex-vivo porcine specimen. We used a tracked stylus to acquire locations of landmarks such as spinous and transverse processes, and calculated the distances between these points and the reconstructed stereovision surface. The resulting accuracy was 0.91 ± 0.58 mm, with an overall computational efficiency of ~ 5s for each image pair. Compared to our previous microscope-based stereovision system, the accuracy and efficiency of HHS are similar while HHS is more practical and functional, and would be more broadly applicable in spine procedures.
Paper Details
Date Published: 8 March 2019
PDF: 7 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511X (8 March 2019); doi: 10.1117/12.2512861
Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)
PDF: 7 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511X (8 March 2019); doi: 10.1117/12.2512861
Show Author Affiliations
Xiaoyao Fan, Dartmouth College (United States)
Maxwell S. Durtschi, Dartmouth College (United States)
Chen Li, Dartmouth College (United States)
Maxwell S. Durtschi, Dartmouth College (United States)
Chen Li, Dartmouth College (United States)
Songbai Ji, Dartmouth College (United States)
Worcester Institute of Polytechnic (United States)
Sohail K. Mirza, Dartmouth College (United States)
Keith D. Paulsen, Dartmouth College and Geisel School of Medicine (United States)
Norris Cotton Cancer Ctr. (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Worcester Institute of Polytechnic (United States)
Sohail K. Mirza, Dartmouth College (United States)
Keith D. Paulsen, Dartmouth College and Geisel School of Medicine (United States)
Norris Cotton Cancer Ctr. (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)
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