Name
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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-85990-1_12 | MICCAI (2) |
Keywords | Field | DocType |
spatio-temporal fluorescence image sequence,event detection,patch-based markov models,time-lapse fluorescence,fluorescence image,original image analysis method,live cell,image sequence,membrane trafficking,membrane transport,fluorescence bioimaging,real image sequence,live state,algorithms,markov model,computer simulation,false alarm rate,molecular dynamic,fluorescence microscopy,fluorescence imaging,3d imaging,image analysis,membrane proteins,markov chains | Fluorescence microscope,Computer vision,False alarm,Pattern recognition,Computer science,Markov model,Markov random field,Markov chain,Protein dynamics,Artificial intelligence,Rab,Real image | Conference |
Volume | Issue | ISSN |
11 | Pt 2 | 0302-9743 |
Citations | PageRank | References |
2 | 0.40 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thierry Pécot | 1 | 28 | 4.39 |
| Charles Kervrann | 2 | 934 | 67.36 |
| Sabine Bardin | 3 | 18 | 2.29 |
| Bruno Goud | 4 | 2 | 0.40 |
| Jean Salamero | 5 | 49 | 6.83 |