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Publications about fluorescence microscopy
Result of the query in the list of publications :
Conference article |
1 - Point-spread function retrieval for fluorescence microscopy.
P. Pankajakshan and L. Blanc-Féraud and Z. Kam and J. Zerubia. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI), Publ. IEEE, Org. IEEE, Boston, USA, June 2009.
Keywords : fluorescence microscopy, point spread function, EM algorithm, Deconvolution.
Copyright : Copyright 2009 IEEE. Published in the 2009 International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2009), scheduled for June 28 - July 1, 2009 in Boston, Massachusetts, U.S.A. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyrights and Permissions / IEEE Service Center / 445 Hoes Lane / P.O. Box 1331 / Piscataway, NJ 08855-1331, USA. Telephone: + Intl. 908-562-3966.
@INPROCEEDINGS{ppankajakshan09a,
|
| author |
= |
{Pankajakshan, P. and Blanc-Féraud, L. and Kam, Z. and Zerubia, J.}, |
| title |
= |
{Point-spread function retrieval for fluorescence microscopy}, |
| year |
= |
{2009}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, |
| publisher |
= |
{IEEE}, |
| organization |
= |
{IEEE}, |
| address |
= |
{Boston, USA}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/39/55/34/PDF/pankajakshan.pdf}, |
| keyword |
= |
{fluorescence microscopy, point spread function, EM algorithm, Deconvolution} |
| } |
Abstract :
In this paper we propose a method for retrieving the Point-Spread Function (PSF) of an imaging system given the observed images of fluorescent microspheres. Theoretically calculated PSFs often lack the experimental or microscope specific signatures while empirically obtained data are either over sized or (and) too noisy. The effect of noise and the influence of the microsphere size can be mitigated from the experimental data by using a Maximum Likelihood Expectation Maximization (MLEM) algorithm. The true experimental parameters can then be estimated by fitting the result to a model based on the scalar diffraction theory. The algorithm was tested on some simulated data and the results obtained validate the usefulness of the approach for retrieving the PSF from measured data. |
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Technical and Research Report |
1 - Space non-invariant point-spread function and its estimation in fluorescence microscopy.
P. Pankajakshan and L. Blanc-Féraud and Z. Kam and J. Zerubia. Research Report 7157, INRIA, December 2009.
Keywords : Confocal Laser Scanning Microscopy, point spread function, Bayesian estimation, MAP estimation, Deconvolution, fluorescence microscopy.
@TECHREPORT{ppankajakshan09c,
|
| author |
= |
{Pankajakshan, P. and Blanc-Féraud, L. and Kam, Z. and Zerubia, J.}, |
| title |
= |
{Space non-invariant point-spread function and its estimation in fluorescence microscopy}, |
| year |
= |
{2009}, |
| month |
= |
{December}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{7157}, |
| url |
= |
{http://hal.archives-ouvertes.fr/inria-00438719/en/}, |
| keyword |
= |
{Confocal Laser Scanning Microscopy, point spread function, Bayesian estimation, MAP estimation, Deconvolution, fluorescence microscopy} |
| } |
Résumé :
Dans ce rapport de recherche, nous rappelons brièvement comment la nature limitée de diffraction de l'objectif d'un microscope optique, et le bruit
intrinsèque peuvent affecter la résolution d'une image observée. Un algorithme de déconvolution aveugle a été proposé en vue de restaurer les fréquences manquants au delà de la limite de diffraction. Cependant, sous d'autres conditions, l'approximation du systéme imageur l'imagerie sans aberration n'est plus valide et donc les aberrations de la phase du front d'onde émergeant d'un médium ne sont plus ignorées. Dans la deuxième partie de
ce rapport de recherche, nous montrons que la distribution d'intensité originelle et la localisation d'un objet peuvent être retrouvées uniquement en obtenant de la phase du front d'onde
réfracté, à partir d'images d'intensité observées. Nous démontrons cela par obtention de la fonction de ou a partir d'une microsphère imagée. Le bruit et l'infl uence de la taille de la
microsphère peuvent être diminués et parfois complètement supprimes des images observées en utilisant un estimateur maximum a posteriori. Néanmoins, a cause de l'incohérence du système d'acquisition, une récupération de phase a partir d'intensités observées n'est possible que si la restauration de la phase est contrainte. Nous avons utilisé l'optique géométrique
pour modéliser la phase du front d'onde réfracté, et nous avons teste l'algorithme sur des images simulées. |
Abstract :
In this research report, we recall briefly how the diffraction-limited nature of an optical microscope's objective, and the intrinsic noise can affect the observed images' resolution. A blind deconvolution algorithm can restore the lost frequencies beyond the diffraction limit. However, under other imaging conditions, the approximation of aberration-free imaging, is not applicable, and the phase aberrations of the emerging wavefront from a specimen immersion medium cannot be ignored any more. We show that an object's location and its original intensity distribution can be recovered by retrieving the refracted wavefront's phase from the observed intensity images. We demonstrate this by retrieving the point-spread function from an imaged microsphere. The noise and the influence of the microsphere size can be mitigated and sometimes completely removed from the observed images by using a maximum a posteriori estimate. However, due to the incoherent nature of the acquisition system, phase retrieval from the observed intensities will be possible only if the phase is constrained. We have used geometrical optics to model the phase of the refracted wavefront, and tested the algorithm on some simulated images. |
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