Reconstruction of 3-D Histology Images by Simultaneous Deformable Registration

  • Marco Feuerstein
  • Hauke Heibel
  • José Gardiazabal
  • Nassir Navab
  • Martin Groher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6892)


The reconstruction of histology sections into a 3-D volume receives increased attention due to its various applications in modern medical image analysis. To guarantee a geometrically coherent reconstruction, we propose a new way to register histological sections simultaneously to previously acquired reference images and to neighboring slices in the stack. To this end, we formulate two potential functions and associate them to the same Markov random field through which we can efficiently find an optimal solution. Due to our simultaneous formulation and the absence of any segmentation step during the reconstruction we can dramatically reduce error propagation effects. This is illustrated by experiments on carefully created synthetic as well as real data sets.


Interpolation Error Angular Error Histology Image Rigid Registration Deformable Registration 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marco Feuerstein
    • 1
  • Hauke Heibel
    • 1
  • José Gardiazabal
    • 1
  • Nassir Navab
    • 1
  • Martin Groher
    • 1
  1. 1.microDimensions and Computer Aided Medical Procedures (CAMP)Technische UniversitätMünchenGermany

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