Accurate Detection in Volumetric Images Using Elastic Registration Based Validation

  • Dominic MaiEmail author
  • Jasmin Dürr
  • Klaus Palme
  • Olaf Ronneberger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8753)


In this paper, we propose a method for accurate detection and segmentation of cells in dense plant tissue of Arabidopsis Thaliana. We build upon a system that uses a top down approach to yield the cell segmentations: A discriminative detection is followed by an elastic alignment of a cell template. While this works well for cells with a distinct appearance, it fails once the detection step cannot produce reliable initializations for the alignment. We propose a validation method for the aligned cell templates and show that we can thereby increase the average precision substantially.


Support Vector Machine Linear Support Vector Machine Cell Segmentation Detection Filter Discriminative Classifier 
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 work was supported by the Excellence Initiative of the German Federal and State Governments: BIOSS Centre for Biological Signalling Studies (EXC 294) and the Bundesministerium für Bildung und Forschung (SYSTEC, 0101-31P5914).


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Dominic Mai
    • 1
    • 2
    Email author
  • Jasmin Dürr
    • 3
  • Klaus Palme
    • 2
    • 3
  • Olaf Ronneberger
    • 1
    • 2
  1. 1.Computer Science DepartmentUniversity of FreiburgFreiburgGermany
  2. 2.BIOSS Centre of Biological Signalling StudiesUniversity of FreiburgFreiburgGermany
  3. 3.Institute for Biologie IIUniversity of FreiburgFreiburgGermany

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