Computational depth-variant imaging for quantitative fluorescence microscopy

Authors

Vimeetha Myneni, University of Memphis
Chrysanthe Preza, University of Memphis

Abstract

We show a performance analysis of a Depth-Variant Expectation Maximization algorithm previously developed for fluorescence microscopy concluding that a small number of point spread functions can be used for an accurate estimation result. © 2009 Optical Society of America.

Publication Title

Optics InfoBase Conference Papers

Recommended Citation

Myneni, V., & Preza, C. (2009). Computational depth-variant imaging for quantitative fluorescence microscopy. Optics InfoBase Conference Papers Retrieved from https://digitalcommons.memphis.edu/facpubs/13605