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International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2014: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 pp 81–88Cite as

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Active Graph Matching for Automatic Joint Segmentation and Annotation of C. elegans

Active Graph Matching for Automatic Joint Segmentation and Annotation of C. elegans

  • Dagmar Kainmueller20,
  • Florian Jug20,
  • Carsten Rother21 &
  • …
  • Gene Myers20 
  • Conference paper
  • 6235 Accesses

  • 16 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 8673)

Abstract

In this work we present a novel technique we term active graph matching, which integrates the popular active shape model into a sparse graph matching problem. This way we are able to combine the benefits of a global, statistical deformation model with the benefits of a local deformation model in form of a second-order random field. We present a new iterative energy minimization technique which achieves empirically good results. This enables us to exceed state-of-the art results for the task of annotating nuclei in 3D microscopic images of C. elegans. Furthermore with the help of the generalized Hough transform we are able to jointly segment and annotate a large set of nuclei in a fully automatic fashion for the first time.

Keywords

  • Manual Segmentation
  • Graph Match
  • Active Shape Model
  • Nucleus Location
  • Active Graph

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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References

  1. Sarov, M., et al.: A Genome-Scale Resource for In Vivo Tag-Based Protein Function Exploration in C. Elegans. Cell 150(4), 855–866 (2012)

    CrossRef  Google Scholar 

  2. Long, F., Peng, H., Liu, X., Kim, S.K., Myers, E.: A 3D Digital Atlas of C. Elegans and its Application to Single-Cell Analyses. Nature Methods 6, 667–672 (2009)

    Google Scholar 

  3. Aerni, S.J., Liu, X., Do, C.B., Gross, S.S., Nguyen, A., Guo, S.D., Long, F., Peng, H., Kim, S.S., Batzoglou, S.: Automated Cellular Annotation for High-resolution Images of Adult C. Elegans. Bioinformatics 29(13), i18–i26 (2013)

    Google Scholar 

  4. Qu, L., Long, F., Liu, X., Kim, S., Myers, E., Peng, H.: Simultaneous Recognition and Segmentation of Cells. Bioinformatics 27(20), 2895–2902 (2011)

    CrossRef  Google Scholar 

  5. Riklin Raviv, T., Ljosa, V., Conery, A.L., Ausubel, F.M., Carpenter, A.E., Golland, P., Wählby, C.: Morphology-guided graph search for untangling objects: C. elegans analysis. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part III. LNCS, vol. 6363, pp. 634–641. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  6. Peng, H., Long, F., Liu, X., Kim, S.K., Myers, E.: Straightening Caenorhabditis Elegans Images. Bioinformatics 24(2), 234–242 (2008)

    CrossRef  Google Scholar 

  7. Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active Shape Models - Their Training and Application. CVIU 61(1), 38–59 (1995)

    Google Scholar 

  8. Torresani, L., Kolmogorov, V., Rother, C.: A dual decomposition approach to feature correspondence. IEEE TPAMI 35(2), 259–271 (2013)

    CrossRef  Google Scholar 

  9. Zhou, F., De La Torre, F.: Deformable graph matching. In: CVPR, pp. 2922–2929 (2013)

    Google Scholar 

  10. Khoshelham, K.: Extending Generalized Hough Transform to Detect 3D Objects in Laser Range Data. In: ISPRS Workshop Laser Scanning, p. 206 (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Max Planck Institute of Molecular Cell Biology and Genetics, Germany

    Dagmar Kainmueller, Florian Jug & Gene Myers

  2. Computer Vision Lab Dresden, Technical University Dresden, Germany

    Carsten Rother

Authors
  1. Dagmar Kainmueller
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  2. Florian Jug
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  3. Carsten Rother
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  4. Gene Myers
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Editor information

Editors and Affiliations

  1. MIT CSAIL, 32 Vassar Street, 02139, Cambridge, MA, USA

    Polina Golland

  2. Department of Radiology, Brigham and Women’s Hospital, 75 Francis St., 02115, Boston, MA, USA

    Nobuhiko Hata

  3. CNRS/Inria Research Unit Visages, IRISA, Campus Universitaire de Beaulieu, 35042, Rennes Cedex, France

    Christian Barillot

  4. Pattern Recognition Lab, University Erlangen-Nuremberg, Martensstr. 3, 91058, Erlangen, Germany

    Joachim Hornegger

  5. Harvard School of Engineering and Applied Sciences, 323 Pierce Hall, 29 Oxford Street, 02138, Cambridge, MA, USA

    Robert Howe

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Kainmueller, D., Jug, F., Rother, C., Myers, G. (2014). Active Graph Matching for Automatic Joint Segmentation and Annotation of C. elegans . In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8673. Springer, Cham. https://doi.org/10.1007/978-3-319-10404-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-10404-1_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10403-4

  • Online ISBN: 978-3-319-10404-1

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