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Erschienen in: International Journal of Computer Assisted Radiology and Surgery 6/2021

10.05.2021 | Original Article

A level-wise spine registration framework to account for large pose changes

verfasst von: Yunliang Cai, Shaoju Wu, Xiaoyao Fan, Jonathan Olson, Linton Evans, Scott Lollis, Sohail K. Mirza, Keith D. Paulsen, Songbai Ji

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 6/2021

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Abstract

Purposes

Accurate and efficient spine registration is crucial to success of spine image guidance. However, changes in spine pose cause intervertebral motion that can lead to significant registration errors. In this study, we develop a geometrical rectification technique via nonlinear principal component analysis (NLPCA) to achieve level-wise vertebral registration that is robust to large changes in spine pose.

Methods

We used explanted porcine spines and live pigs to develop and test our technique. Each sample was scanned with preoperative CT (pCT) in an initial pose and rescanned with intraoperative stereovision (iSV) in a different surgical posture. Patient registration rectified arbitrary spinal postures in pCT and iSV into a common, neutral pose through a parameterized moving-frame approach. Topologically encoded depth projection 2D images were then generated to establish invertible point-to-pixel correspondences. Level-wise point correspondences between pCT and iSV vertebral surfaces were generated via 2D image registration. Finally, closed-form vertebral level-wise rigid registration was obtained by directly mapping 3D surface point pairs. Implanted mini-screws were used as fiducial markers to measure registration accuracy.

Results

In seven explanted porcine spines and two live animal surgeries (maximum in-spine pose change of 87.5 mm and 32.7 degrees averaged from all spines), average target registration errors (TRE) of 1.70  ±  0.15 mm and 1.85 ± 0.16 mm were achieved, respectively. The automated spine rectification took 3–5 min, followed by an additional 30 secs for depth image projection and level-wise registration.

Conclusions

Accuracy and efficiency of the proposed level-wise spine registration support its application in human open spine surgeries. The registration framework, itself, may also be applicable to other intraoperative imaging modalities such as ultrasound and MRI, which may expand utility of the approach in spine registration in general.

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Metadaten
Titel
A level-wise spine registration framework to account for large pose changes
verfasst von
Yunliang Cai
Shaoju Wu
Xiaoyao Fan
Jonathan Olson
Linton Evans
Scott Lollis
Sohail K. Mirza
Keith D. Paulsen
Songbai Ji
Publikationsdatum
10.05.2021
Verlag
Springer International Publishing
Erschienen in
International Journal of Computer Assisted Radiology and Surgery / Ausgabe 6/2021
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-021-02395-0

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