Abstract
PURPOSE: Point-set registration for interventional tools requires well-defined points to be present on these tools. In this work, an algorithm is proposed which uses planes, lines, and points for registration when point-set registration is not feasible. METHODS: The proposed algorithm matches points, lines, and planes in each coordinate system, uses invariant features for initial registration, and optimizes the registration iteratively. For validation, simulated data with known ground-truth and real surgical tool registration data using point-set registration as ground-truth were created to evaluate the algorithm’s accuracy. RESULTS: The proposed algorithm is equally as accurate as point-set registration, and the difference between the registrations is less than the noise in the tracking system. CONCLUSION: The proposed algorithm is a viable alternative when point-set registration cannot be performed.
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References
Besl, P.J., McKay, N.D.: A Method for Registration of 3D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14, 239–256 (1992)
Carbajal, G., et al.: Improving N-wire phantom-based freehand ultrasound calibration. International Journal of Computer Assisted Radiology and Surgery 8, 1063–1072 (2013)
Chen, T.K., et al.: A Real-Time Freehand Ultrasound Calibration System with Automatic Accuracy Feedback and Control. Ultrasound in Medicine & Biology 35(1), 79–93 (2009)
Fitzgibbon, A.W.: Robust Registration of 2D and 3D Point Sets. Image and Vision Computing 21, 1145–1153 (2003)
Fitzpatrick, J.M., West, J.B., Maurer, C.R.: Predicting Error in Rigid-Body Registration. IEEE Transactions on Medical Imaging 17, 694–702 (1998)
Foroughi, P., Taylor, R., Fichtinger, G.: Revisited Initialization for 3D Bone Registration. In: Proceedings of SPIE (2008)
Jain, A.K., et al.: FTRAC - A robust fluoroscopic tracking fiducial. Medical Physics 32(10), 3185–3198 (2005)
Lee, S., Fichtinger, G., Chirikjian, G.S.: Numerical algorithms for spatial registration of line fiducial from cross-sectional images. Medical Physics 29(8), 1881–1891 (2002)
Li, H., Hartley, R.: The 3D-3D Registration Problem Revisited. In: IEEE International Conference on Computer Vision (2007)
Meyer, C.R., et al.: Simultaneous Usage of Homologous Points, Lines, and Planes for Optimal 3D, Linear Registration of Multimodality Imaging Data. IEEE Transactions on Medical Imaging 14, 1–11 (1995)
Olsson, C., Kahl, F., Oskarsson, M.: Branch-and-Bound Methods for Euclidean Registration Problems. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(5), 783–794 (2009)
Shamir, R., Freiman, M., Joskowicz, L., Shoham, M., Zehavi, E., Shoshan, Y.: Robot-Assisted Image-Guided Targeting for Minimally Invasive Neurosurgery: Planning, Registration, and In-vitro Experiment. In: Duncan, J.S., Gerig, G., et al. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 131–138. Springer, Heidelberg (2005)
Thirion, J.P.: Extremal Points: Definition and Application to 3D Image Registration. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1994)
Ungi, T., et al.: Perk Tutor: An open-source training platform for ultrasound-guided needle insertions. IEEE Transactions on Biomedical Engineering 59(12), 3475–3481 (2012)
Walsh, R., et al.: Design of a tracked ultrasound calibration made of LEGO bricks. In: SPIE Medical Imaging (2014)
Xiao, G., Ong, S.H., Foong, K.W.C.: Efficient Partial-Surface Registration for 3D Objects. Computer Vision and Image Understanding 98, 271–293 (2005)
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Holden, M.S., Fichtinger, G. (2014). Linear Object Registration of Interventional Tools. In: Linte, C.A., Yaniv, Z., Fallavollita, P., Abolmaesumi, P., Holmes, D.R. (eds) Augmented Environments for Computer-Assisted Interventions. AE-CAI 2014. Lecture Notes in Computer Science, vol 8678. Springer, Cham. https://doi.org/10.1007/978-3-319-10437-9_13
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DOI: https://doi.org/10.1007/978-3-319-10437-9_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10436-2
Online ISBN: 978-3-319-10437-9
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