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  HIERARCHIVAL MARKOV RANDOM FIELDS FOR MAST CELL SEGMENTATION IN ELECTRON MICROSCOPIC RECORDINGS

Keuper, M., Schmidt, T., Rodriguez-Franco, M., Schamel, W., Brox, T., Burkhardt, H., et al. (2011). HIERARCHIVAL MARKOV RANDOM FIELDS FOR MAST CELL SEGMENTATION IN ELECTRON MICROSCOPIC RECORDINGS. International Symposium on Biomedical Imaging, 973, 973-978.

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 Creators:
Keuper, Margret, Author
Schmidt, Thorsten, Author
Rodriguez-Franco, Marta, Author
Schamel, Wolfgang1, Author              
Brox, Thomas, Author
Burkhardt, Hans, Author
Ronneberger, Olaf, Author
Affiliations:
1Research Group and Chair of Molecular Immunology of the University of Freiburg, Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society, ou_2243645              

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Free keywords: Segmentation; SVM; MRF; hierachical models
 Abstract: We present a hierarchical Markov Random Field (HMRF) for multi-label image segmentation. With such a hierarchical model, we can incorporate global knowledge into our segmentation algorithm. Solving the MRF is formulated as a MAX-SUM problem for which there exist efficient solvers based on linear programming. We show that our method allows for automatic segmentation of mast cells and their cell organelles from 2D electron microscopic recordings. The presented HMRF outperforms clasical MRFs as well as local classification approaches wrt. pixelwise segmentation accuracy. Additionally, the resulting segmentations are much more consistent regarding the region compactness.

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Language(s): eng - English
 Dates: 2011
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: eDoc: 577488
 Degree: -

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Title: International Symposium on Biomedical Imaging: From Nano To Macro
Place of Event: -
Start-/End Date: 2011 - 2011

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Title: International Symposium on Biomedical Imaging
  Alternative Title : ICBI
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: 973 Start / End Page: 973 - 978 Identifier: -