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Fluorescence microscopy imaging denoising with Log-Euclidean priors and photobleaching compensation

dc.contributor.authorRodrigues, Isabel Maria Cabrita
dc.contributor.authorSanches, João
dc.date.accessioned2011-11-24T18:26:23Z
dc.date.available2011-11-24T18:26:23Z
dc.date.issued2010-02-17
dc.description.abstractFluorescent protein microscopy imaging is nowadays one of the most important tools in biomedical research. However, the resulting images present a low signal to noise ratio and a time intensity decay due to the photobleaching effect. This phenomenon is a consequence of the decreasing on the radiation emission efficiency of the tagging protein. This occurs because the fluorophore permanently loses its ability to fluoresce, due to photochemical reactions induced by the incident light. The Poisson multiplicative noise that corrupts these images, in addition with its quality degradation due to photobleaching, make long time biological observation processes very difficult. In this paper a denoising algorithm for Poisson data, where the photobleaching effect is explicitly taken into account, is described. The algorithm is designed in a Bayesian framework where the data fidelity term models the Poisson noise generation process as well as the exponential intensity decay caused by the photobleaching. The prior term is conceived with Gibbs priors and log-Euclidean potential functions, suitable to cope with the positivity constrained nature of the parameters to be estimated. Monte Carlo tests with synthetic data are presented to characterize the performance of the algorithm. One example with real data is included to illustrate its application.por
dc.identifier.citationRODRIGUES, Isabel; SANCHES, João – Fluorescence microscopy imaging denoising with Log-Euclidean priors and photobleaching compensation. In 2009 16th IEEE International Conference on Image Processing. Cairo, Egipt: IEEE, 2009. ISBN 978-1-4244-5654-3. Vol. 1-6. Pp. 809-812.por
dc.identifier.doi10.1109/ICIP.2009.5414440
dc.identifier.eissn2381-8549
dc.identifier.isbn978-1-4244-5654-3
dc.identifier.isbn978-1-4244-5653-6
dc.identifier.isbn978-1-4244-5655-0
dc.identifier.issn1522-4880
dc.identifier.urihttp://hdl.handle.net/10400.21/569
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherIEEEpor
dc.subjectPhotobleachingpor
dc.subjectPoisson denoisingpor
dc.subjectBayesianpor
dc.subjectTotal variationpor
dc.subjectLog-Euclidean potentialspor
dc.titleFluorescence microscopy imaging denoising with Log-Euclidean priors and photobleaching compensationpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceNew Yorkpor
oaire.citation.endPage812por
oaire.citation.startPage809por
oaire.citation.title2009 16th IEEE International Conference on Image Processingpor
oaire.citation.volume1-6
rcaap.rightsrestrictedAccesspor
rcaap.typearticlepor

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