Journal
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
Volume 14, Issue 10, Pages 1725-1739Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s11548-019-02024-x
Keywords
Registration; Capture range; Intensity-based; Spine; Pedicle screw; 2D-3D; Implant verification
Funding
- Canadian Natural Sciences and Engineering Research Council (NSERC)
- Canadian Institutes of Health Research (CIHR)
- Institute for Computing, Information and Cognitive Systems
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Purpose Although multiple algorithms have been reported that focus on improving the accuracy of 2D-3D registration techniques, there has been relatively little attention paid to quantifying their capture range. In this paper, we analyze the capture range for a number of variant formulations of the 2D-3D registration problem in the context of pedicle screw insertion surgery. Methods We tested twelve 2D-3D registration techniques for capture range under different clinically realistic conditions. A registration was considered as successful if its error was less than 2 mm and 2 degrees in 95% of the cases. We assessed the sensitivity of capture range to a variety of clinically realistic parameters including: X-ray contrast, number and configuration of X-rays, presence or absence of implants in the image, inter-subject variability, intervertebral motion and single-level vs multi-level registration. Results Gradient correlation + Powell optimizer had the widest capture range and the least sensitivity to X-ray contrast. The combination of 4 AP + lateral X-rays had the widest capture range (725 mm(2)). The presence of implant projections significantly reduced the registration capture range (up to 84%). Different spine shapes resulted in minor variations in registration capture range (SD 78 mm(2)). Intervertebral angulations of less than 1.5 degrees had modest effects on the capture range. Conclusions This paper assessed capture range of a number of variants of intensity-based 2D-3D registration algorithms in clinically realistic situations (for the use in pedicle screw insertion surgery). We conclude that a registration approach based on the gradient correlation similarity and the Powell's optimization algorithm, using a minimum of two C-arm images, is likely sufficiently robust for the proposed application.
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