Patch-Based Markov Models for Event Detection in Fluorescence Bioimaging

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.
Type de document :
Communication dans un congrès
MICCAI - 11th International conference on medical image computing and computer assisted intervention - 2008, Sep 2008, New York, United States. 2008
Liste complète des métadonnées

Littérature citée [11 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-00919712
Contributeur : Thierry Pécot <>
Soumis le : mardi 17 décembre 2013 - 11:25:24
Dernière modification le : mercredi 11 avril 2018 - 01:53:58
Document(s) archivé(s) le : lundi 17 mars 2014 - 22:41:33

Fichier

chp_3A10.1007_2F978-3-540-8599...
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00919712, version 1

Collections

Citation

Thierry Pécot, Charles Kervrann, Sabine Bardin, Bruno Goud, Jean Salamero. Patch-Based Markov Models for Event Detection in Fluorescence Bioimaging. MICCAI - 11th International conference on medical image computing and computer assisted intervention - 2008, Sep 2008, New York, United States. 2008. 〈hal-00919712〉

Partager

Métriques

Consultations de la notice

311

Téléchargements de fichiers

80