Depth-variant maximum-likelihood restoration for three-dimensional fluorescence microscopy

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...

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Bibliographic Details
Published inJournal of the Optical Society of America. A, Optics, image science, and vision Vol. 21; no. 9; p. 1593
Main Authors Preza, Chrysanthe, Conchello, José-Angel
Format Journal Article
LanguageEnglish
Published United States 01.09.2004
Subjects
Algorithms
Computer Simulation
Image Processing, Computer-Assisted
Imaging, Three-Dimensional
Microscopy, Fluorescence
Models, Theoretical
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Summary: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.
ISSN:1084-7529
DOI:10.1364/JOSAA.21.001593