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Patch-Based Markov Models for Event Detection in Fluorescence Bioimaging

  • Thierry Pécot
  • Charles Kervrann
  • Sabine Bardin
  • Bruno Goud
  • Jean Salamero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5242)

Abstract

The study of protein dynamics is essential for understanding the multi-molecular complexes at subcellular levels. Fluorescent Protein (XFP)-tagging and time-lapse fluorescence microscopy enable to observe molecular dynamics and interactions in live cells, unraveling the live states of the matter. Original image analysis methods are then required to process challenging 2D or 3D image sequences. Recently, tracking methods that estimate the whole trajectories of moving objects have been successfully developed. In this paper, we address rather the detection of meaningful events in spatio-temporal fluorescence image sequences, such as apparent stable “stocking areas” involved in membrane transport. We propose an original patch-based Markov modeling to detect spatial irregularities in fluorescence images with low false alarm rates. This approach has been developed for real image sequences of cells expressing XFP-tagged Rab proteins, known to regulate membrane trafficking.

Keywords

Markov Random Field False Alarm Probability Markov Random Field Model Real Image Sequence Gibbs Model 
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.

Supplementary material

978-3-540-85990-1_12_MOESM1_ESM.zip (3 mb)
Electronic Supplementary Material (3,075 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Thierry Pécot
    • 1
    • 2
  • Charles Kervrann
    • 1
    • 2
  • Sabine Bardin
    • 3
  • Bruno Goud
    • 3
  • Jean Salamero
    • 3
    • 4
  1. 1.INRIA Rennes - Bretagne AtlantiqueRennes
  2. 2.INRA, UR341 Mathématiques et informatique appliquéesJouy-en-JosasFrance
  3. 3.UMR 144 CNRS - Institut CurieParisFrance
  4. 4.“Cell and Tissue Imaging Facility” IBISA, Institut CurieParisFrance

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