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High Order Slice Interpolation for Medical Images

Part of the Lecture Notes in Computer Science book series (LNIP,volume 10557)

Abstract

In this paper we introduce a high order object- and intensity-based method for slice interpolation. Similar structures along the slices are registered using a symmetric similarity measure to calculate displacement fields between neighboring slices. For the intensity-based and curvature-regularized registration no manual landmarks are needed but the structures between two subsequent slices have to be similar. The set of displacement fields is used to calculate a natural spline interpolation for structural motion that avoids kinks. Along every correspondence point trajectory, again high order intensity interpolating splines are calculated for gray values. We test our method on an artificial scenario and on real MR images. Leave-one-slice-out evaluations show that the proposed method improves the slice estimation compared to piecewise linear registration-based slice interpolation and cubic interpolation.

Keywords

  • Slice interpolation
  • Image registration
  • Splines

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Notes

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Correspondence to Antal Horváth .

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Horváth, A., Pezold, S., Weigel, M., Parmar, K., Cattin, P. (2017). High Order Slice Interpolation for Medical Images. In: Tsaftaris, S., Gooya, A., Frangi, A., Prince, J. (eds) Simulation and Synthesis in Medical Imaging. SASHIMI 2017. Lecture Notes in Computer Science(), vol 10557. Springer, Cham. https://doi.org/10.1007/978-3-319-68127-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-68127-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68126-9

  • Online ISBN: 978-3-319-68127-6

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