Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images

  • C. N. Straehle
  • U. Köthe
  • G. Knott
  • F. A. Hamprecht
Conference paper

DOI: 10.1007/978-3-642-23623-5_82

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6891)
Cite this paper as:
Straehle C.N., Köthe U., Knott G., Hamprecht F.A. (2011) Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. In: Fichtinger G., Martel A., Peters T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6891. Springer, Berlin, Heidelberg

Abstract

Interactive segmentation algorithms should respond within seconds and require minimal user guidance. This is a challenge on 3D neural electron microscopy images. We propose a supervoxel-based energy function with a novel background prior that achieves these goals. This is verified by extensive experiments with a robot mimicking human interactions. A graphical user interface offering access to an open source implementation of these algorithms is made available.

Keywords

electron microscopy seeded segmentation interactive segmentation graph cut watershed supervoxel 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • C. N. Straehle
    • 1
  • U. Köthe
    • 1
  • G. Knott
    • 2
  • F. A. Hamprecht
    • 1
  1. 1.University of HeidelbergHeidelbergGermany
  2. 2.Ecole Polytechnique FédéraleLausanneSwitzerland

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