Status: Bibliographieeintrag
Standort: ---
Exemplare:
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| Online-Ressource |
Verfasst von: | Godinez, William J. [VerfasserIn]  |
| Lampe, Marko [VerfasserIn]  |
| Koch, Peter [VerfasserIn]  |
| Eils, Roland [VerfasserIn]  |
| Müller, Barbara [VerfasserIn]  |
| Rohr, Karl [VerfasserIn]  |
Titel: | Identifying virus-cell fusion in two-channel fluorescence microscopy image sequences based on a layered probabilistic approach |
Verf.angabe: | William J. Godinez* (student member, IEEE), Marko Lampe, Peter Koch, Roland Eils, Barbara Müller, and Karl Rohr, (member, IEEE) |
Umfang: | 23 S. |
Fussnoten: | Gesehen am 05.09.2018 |
Titel Quelle: | Enthalten in: Institute of Electrical and Electronics Engineers: IEEE transactions on medical imaging |
Jahr Quelle: | 2012 |
Band/Heft Quelle: | 31(2012), 9, S. 1786-1808 |
ISSN Quelle: | 1558-254X |
Abstract: | The entry process of virus particles into cells is decisive for infection. In this work, we investigate fusion of virus particles with the cell membrane via time-lapse fluorescence microscopy. To automatically identify fusion for single particles based on their intensity over time, we have developed a layered probabilistic approach. The approach decomposes the action of a single particle into three abstractions: the intensity over time, the underlying temporal intensity model, as well as a high level behavior. Each abstraction corresponds to a layer and these layers are represented via stochastic hybrid systems and hidden Markov models. We use a maxbelief strategy to efficiently combine both representations. To compute estimates for the abstractions we use a hybrid particle filter and the Viterbi algorithm. Based on synthetic image sequences, we characterize the performance of the approach as a function of the image noise. We also characterize the performance as a function ofthe tracking error. We have also successfully applied the approach to real image sequences displaying pseudotyped HIV-1 particles in contact with host cells and compared the experimental results with ground truth obtained by manual analysis. |
DOI: | doi:10.1109/TMI.2012.2203142 |
URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Verlag: http://dx.doi.org/10.1109/TMI.2012.2203142 |
| Verlag: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6213119&tag=1 |
| DOI: https://doi.org/10.1109/TMI.2012.2203142 |
Datenträger: | Online-Ressource |
Sprache: | eng |
K10plus-PPN: | 1580689507 |
Verknüpfungen: | → Zeitschrift |
Identifying virus-cell fusion in two-channel fluorescence microscopy image sequences based on a layered probabilistic approach / Godinez, William J. [VerfasserIn] (Online-Ressource)
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