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access icon openaccess Estimation of surgical tool-tip tracking error distribution in coordinate reference frame involving pivot calibration uncertainty

Accurate understanding of surgical tool-tip tracking error is important for decision making in image-guided surgery. In this Letter, the authors present a novel method to estimate/model surgical tool-tip tracking error in which they take pivot calibration uncertainty into consideration. First, a new type of error that is referred to as total target registration error (TTRE) is formally defined in a single-rigid registration. Target localisation error (TLE) in two spaces to be registered is considered in proposed TTRE formulation. With first-order approximation in fiducial localisation error (FLE) or TLE magnitude, TTRE statistics (mean, covariance matrix and root-mean-square (RMS)) are then derived. Second, surgical tool-tip tracking error in optical tracking system (OTS) frame is formulated using TTRE when pivot calibration uncertainty is considered. Finally, TTRE statistics of tool-tip in OTS frame are then propagated relative to a coordinate reference frame (CRF) rigid-body. Monte Carlo simulations are conducted to validate the proposed error model. The percentage passing statistical tests that there is no difference between simulated and theoretical mean and covariance matrix of tool-tip tracking error in CRF space is more than 90% in all test cases. The RMS percentage difference between simulated and theoretical tool-tip tracking error in CRF space is within 5% in all test cases.

References

    1. 1)
      • 24. Bruns, T.L., Webster III, R.J.: ‘An image guidance system for positioning robotic cochlear implant insertion tools’. Proc. of SPIE, 2017, 10135, pp. 101350O-1101350O-6.
    2. 2)
    3. 3)
      • 1. Yaniv, Z.: ‘Registration for orthopaedic interventions’, In Zheng, G., Li, S. (Eds.): ‘Computational radiology for orthopaedic interventions’ (Springer International Publishing, 2016), pp. 4170.
    4. 4)
    5. 5)
      • 17. Yaniv, Z.: ‘Which pivot calibration?SPIE Medical Imaging, 2015, pp. 941527941527-9.
    6. 6)
      • 12. Datteri, R., Dawant, B.: ‘Estimation and reduction of target registration error’. Medical Image Computing and Computer-Assisted Intervention-MICCAI, 2012, pp. 139146.
    7. 7)
    8. 8)
      • 20. Simpson, A.L., Dillon, N.P., Miga, M.I., et al: ‘A framework for measuring TRE at the tip of an optically tracked pointing stylus’. SPIE Medical Imaging, 2013, (2013), pp. 867114867121.
    9. 9)
      • 15. Min, Z., Meng, M.Q.H.: ‘General first-order TRE model when using a coordinate reference frame for rigid point-based registration’. 2017 IEEE 14th Int. Symp. Biomedical Imaging (ISBI 2017), 2017, pp. 169173.
    10. 10)
    11. 11)
      • 16. Wiles, A.D., Peters, T.M.: ‘Improved statistical TRE model when using a reference frame’. Int. Conf. on Medical Image Computing and Computer-Assisted Intervention, 2007.
    12. 12)
    13. 13)
      • 23. Ma, B., Choi, J., Huai, H.M.: ‘Target registration error for rigid shape-based registration with heteroscedastic noise’. SPIE Medical Imaging, 2014, pp. 90360U90360U.
    14. 14)
      • 22. Balachandran, R., Fitzpatrick, J.M.: ‘Iterative solution for rigid-body point-based registration with anisotropic weighting’. SPIE Medical Imaging, 2009, pp. 72613D72613D.
    15. 15)
    16. 16)
      • 13. Fitzpatrick, J.M.: ‘Rigid point registration circuits’. SPIE Medical Imaging, 2014, pp. 90362P90362P.
    17. 17)
    18. 18)
    19. 19)
    20. 20)
      • 11. Datteri, R., Dawant, B.M.: ‘Estimation of rigid-body registration quality using registration networks’. SPIE Medical Imaging, 2012, pp. 831419831419.
    21. 21)
      • 21. Simpson, A.L., Ma, B., Ellis, R.E., et al: ‘Uncertainty propagation and analysis of image-guided surgery’. SPIE Medical Imaging, 2011, pp. 79640H79640H-7.
    22. 22)
    23. 23)
    24. 24)
      • 25. Dillon, N.P., Siebold, M.A., Mitchell, J.E., et al: ‘Increasing safety of a robotic system for inner ear surgery using probabilistic error modeling near vital anatomy’. SPIE Medical Imaging, 2016, pp. 97861G97861G.
    25. 25)
      • 18. Ma, B., Banihaveb, N., Choi, J., et al: ‘Is pose-based pivot calibration superior to sphere fitting?SPIE Medical Imaging, 2017, pp. 101351U101351U.
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