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

• Published in: Journal 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
• Language: English
• Published: United States 01.09.2004
• Subjects: Algorithms; Computer Simulation; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Microscopy, Fluorescence; Models, Theoretical
• DOI: 10.1364/JOSAA.21.001593
• ISSN: 1084-7529

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.