Computational imaging for 3D fluorescence microscopy
Abstract
Computational imaging approaches have been developed to address depth variability in 3D fluorescence microscopy of imaging of thick samples, using depth-variant restoration and/or point-spread function engineering. Results from simulated and experimental data are presented. © 2014 Optical Society of America.
Publication Title
Optics InfoBase Conference Papers
Recommended Citation
Preza, C. (2014). Computational imaging for 3D fluorescence microscopy. Optics InfoBase Conference Papers https://doi.org/10.1364/isa.2014.iw2c.1
COinS
