Hooman Esfandiari1, Carolyn Anglin2, Pierre Guy3, John Street4, Simon Weidert5, Antony J Hodgson6. 1. Surgical Technologies Lab, Centre for Hip Health and Mobility, Biomedical Engineering, University of British Columbia, H.N. Ho Research Centre, 5th Floor, 2635 Laurel St, Vancouver, BC, V5Z 1M9, Canada. hooman.esfandiari@ubc.ca. 2. Biomedical Engineering, Civil Engineering, McCaig Institute for Bone and Joint Health, University of Calgary, 2500 University Dr NW, Calgary, AB, T2N 1N4, Canada. 3. Department of Orthopaedic Surgery, Robert H.N. Ho Research Centre, University of British Columbia, 5th Floor, 2635 Laurel St, Vancouver, BC, V5Z 1M9, Canada. 4. Combined Neurosurgical and Orthopaedic Spine Program, Blusson Spinal Cord Center, University of British Columbia, Floor 6-818 10 Ave W, Vancouver, BC, V5Z 1M9, Canada. 5. Department of General, Trauma and Reconstructive Surgery, Hospital of the University of Munich, Klinikum Grosshadern, Marchioninistr.15, 81377, Munich, Germany. 6. Surgical Technologies Lab, Centre for Hip Health and Mobility, Mechanical Engineering Department, University of British Columbia, 6250 Applied Science Lane, Vancouver, BC, V7T 1Z4, Canada.
Abstract
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° 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 mm2). 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 mm2). Intervertebral angulations of less than 1.5° 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.
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° 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 mm2). 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 mm2). Intervertebral angulations of less than 1.5° 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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