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Publication Detail
2D-3D registration accuracy estimation for optimised planning of image-guided pancreatobiliary interventions
  • Publication Type:
  • Authors:
    Hu Y, Bonmati E, Gibson E, Hipwell JH, Hawkes DJ, Bandula S, Pereira SP, Barratt DC
  • Publication date:
  • Pagination:
    516, 524
  • Published proceedings:
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Volume:
    9900 LNCS
  • ISBN-13:
  • Status:
  • Print ISSN:
© Springer International Publishing AG 2016. We describe a fast analytical method to estimate landmark-based 2D-3D registration accuracy to aid the planning of pancreatobiliary interventions in which ERCP images are combined with information from diagnostic 3D MR or CT images. The method analytically estimates a target registration error (TRE),accounting for errors in the manual selection of both 2D- and 3D landmarks,that agrees with Monte Carlo simulation to within 4.5 ± 3.6 % (mean ± SD). We also show how to analytically estimate a planning uncertainty incorporating uncertainty in patient positioning,and utilise it to support ERCP-guided procedure planning by selecting the optimal patient position and X-ray C-arm orientation that minimises the expected TRE. Simulated- and derived planning uncertainties agreed to within 17.9 ± 9.7 % when the root-mean-square error was less than 50°. We demonstrate the feasibility of this approach on clinical data from two patients.
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