Skip to main content

Binary Image Inpainting with Interpolation-Enhanced Diffeomorphic Demons Registration

Application to Segmentation Defects of Proximal Femora

  • 2410 Accesses

Part of the Informatik aktuell book series (INFORMAT)

Abstract

There is a wide range of segmentation methods for bone structures in CT images. Many of these methods are declared as automatic, but it is not guaranteed, that the resulting segmentation labels the volume of interest correctly in any case. This work presents a technique, which assists the user with the necessary corrections of the segmentation errors. The procedure must be started manually, but the following steps are fully automatic. First, a similar, correct segmentation is selected from a database, which is used to mask the defects. Then the selected segmentation is registered onto the defect one using the diffeomorphic demons algorithm. Thereby, the region inside the mask is excluded from registration but the displacement field is interpolated. The method has been implemented and tested for segmentations of the proximal femur head, but can easily be transferred to segmentations of other bone regions.

Keywords

  • Proximal Femur
  • Binary Image
  • Segmentation Error
  • Rigid Registration
  • Statistical Shape Model

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-662-46224-9_19
  • Chapter length: 6 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   79.99
Price excludes VAT (USA)
  • ISBN: 978-3-662-46224-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   89.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bankman IN. Handbook of Medical Imaging: Processing and Analysis. Burlington: Academic Press; 2009.

    Google Scholar 

  2. Kronman A, Joskowicz L. Image segmentation errors correction by mesh segmentation and deformation. Med Image Comput Comput Assist Interv. 2013;16:206–13.

    Google Scholar 

  3. Henn S, Hoemke L, Witsch K. A generalized image registration framework using incomplete image information - with application to lesion mapping. In: Mathematics in Industry. vol. 10. Springer; 2006. p. 3–25.

    Google Scholar 

  4. Lamecker H, Pennec X. Atlas to image-with-tumor registration based on demons and deformation inpainting. Proc MICCAI. 2010.

    Google Scholar 

  5. Thirion JP. Image matching as a diffusion process: an analogy with Maxwell’s demons. Med Image Anal. 1998;2:243–60.

    CrossRef  Google Scholar 

  6. Press WH, et al. Numerical Recipes. New York: Cambridge University Press; 2007.

    Google Scholar 

  7. Vercauteren T, et al. Diffeomorphic demons: efficient non-parametric image registration. NeuroImage. 2009;45:61–72.

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Friedberger .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Friedberger, A., Museyko, O., Engelke, K. (2015). Binary Image Inpainting with Interpolation-Enhanced Diffeomorphic Demons Registration. In: Handels, H., Deserno, T., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2015. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46224-9_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-46224-9_19

  • Published:

  • Publisher Name: Springer Vieweg, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46223-2

  • Online ISBN: 978-3-662-46224-9

  • eBook Packages: Computer Science and Engineering (German Language)