Depth-variant maximum-likelihood restoration for three-dimensional fluorescence microscopy
JOSA A, Vol. 21, Issue 9, pp. 1593-1601 (2004)
http://dx.doi.org/10.1364/JOSAA.21.001593
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Abstract
We derive an algorithm for maximum-likelihood image estimation on the basis of the expectation-maximization (EM) formalism by using a new approximate model for depth-varying image formation for optical sectioning microscopy. This new strata-based model incorporates spherical aberration that worsens as the microscope is focused deeper under the cover slip and is the result of the refractive-index mismatch between the immersion medium and the mounting medium of the specimen. Images of a specimen with known geometry and refractive index show that the model captures the main features of the image. We analyze the performance of the depth-variant EM algorithm with simulations, which show that the algorithm can compensate for image degradation changing with depth.
© 2004 Optical Society of America
OCIS Codes
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(100.6890) Image processing : Three-dimensional image processing
(170.6900) Medical optics and biotechnology : Three-dimensional microscopy
(180.2520) Microscopy : Fluorescence microscopy
(180.6900) Microscopy : Three-dimensional microscopy
Citation
Chrysanthe Preza and José-Angel Conchello, "Depth-variant maximum-likelihood restoration for three-dimensional fluorescence microscopy," J. Opt. Soc. Am. A 21, 1593-1601 (2004)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-21-9-1593
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