Abstract
Advancements in intra-operative visualization have accelerated the adoption of C-Arm Fluoroscopy imaging modalities within Image-Guided Spine Surgery (IGSS) procedures. The proposed research provides a novel technique for improving precision in IGSS via EnPrO by refining the mapping of 2D fluoroscopic images to the patient’s anatomy. The fundamental strategy is to minimize reprojection error (RPE) by picking optimal fiducial sites via weighted norm approximation. In EnPrO, we propose two methods to perform optimization for fiducial weights, namely, using fiducial coordinates and using a camera projection matrix (CPM). Using EnPrO, the C-Arm imaging distortion that contributes to increasing RPE can be identified and excluded from the IGSS calibration procedure. Using EnPrO, fiducials were chosen based on weights obtained using the fiducial coordinates and the CPM clearly showed an average RPE decrease of 6.96% and 8.36% respectively. The implementation of the project can be found in this repository: EnPrO - GitHub
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References
Bertelsen, A., Garin-Muga, A., Echeverría, M., Gómez, E., Borro, D.: Distortion correction and calibration of intra-operative spine X-ray images using a constrained DLT algorithm. Comput. Med. Imaging Graph. 38(7), 558–568 (2014)
El hazzat, S., Saaidi, A., Karam, A., Satori, K.: Incremental multi-view 3D reconstruction starting from two images taken by a stereo pair of cameras. 3D Res. 6(1–18) (2015)
Foley, K.T., Simon, D.A., Rampersaud, Y.R.: Virtual fluoroscopy: computer-assisted fluoroscopic navigation. Spine 26(4), 347–351 (2001)
Grant, M., Boyd, S.: Graph implementations for nonsmooth convex programs. In: Blondel, V., Boyd, S., Kimura, H. (eds.) Recent Advances in Learning and Control, pp. 95–110. Springer-Verlag Limited, Lecture Notes in Control and Information Sciences (2008)
Grant, M., Boyd, S.: CVX: Matlab software for disciplined convex programming, version 2.1. https://cvxr.com/cvx (Mar 2014)
Heemeyer, F., Choudhary, A., Desai, J.P.: Pose-aware C-arm calibration and image distortion correction for guidewire tracking and image reconstruction. In: 2020 International Symposium on Medical Robotics (ISMR), pp. 181–187 (2020)
Holly, L.T.: Image-guided spinal surgery. Int. J. Med. Robot. Comput. Assist. Surg. 2(1), 7–15 (2006)
Hsieh, J.C., et al.: Accuracy of intraoperative computed tomography image-guided surgery in placing pedicle and pelvic screws for primary versus revision spine surgery. Neurosurg. Focus 36(3), E2 (2014)
Mai, F., Hung, Y.: Augmented lagrangian approach for projective reconstruction from multiple views. In: 18th International Conference on Pattern Recognition (ICPR’06), IEEE (2006)
Purayath, A., Maik, V., Abhilash, Lakshmanan, M., Sivaprakasam, M.: A novel spatio\(^2\)-frequency blob detection algorithm for enhancing precision in image guided surgery (2024)
Sommer, F., Goldberg, J.L., McGrath, L., Kirnaz, S., Medary, B., Härtl, R.: Image guidance in spinal surgery: a critical appraisal and future directions. Int. J. Spine Surg. 15(s2), S74–S86 (2021)
Tungadio, D.H., Numbi, B.P., Siti, M.W., Jordaan, J.A.: Weighted least squares and iteratively reweighted least squares comparison using particle swarm optimization algorithm in solving power system state estimation. In: Africon, IEEE (2013)
Zhang, X., Zheng, G.: Robust automatic detection and removal of fiducial projections in fluoroscopy images: an integrated solution. In: 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE (2008)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)
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Parthasarathy, S. et al. (2024). EnPrO: Enhancing Precision Through Optimization in Image-Guided Spine Surgical Procedures. In: Drechsler, K., Oyarzun Laura, C., Freiman, M., Chen, Y., Wesarg, S., Erdt, M. (eds) Clinical Image-Based Procedures. CLIP 2024. Lecture Notes in Computer Science, vol 15196. Springer, Cham. https://doi.org/10.1007/978-3-031-73083-2_5
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DOI: https://doi.org/10.1007/978-3-031-73083-2_5
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