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
We derive an algorithm for maximum-likelihood image estimation on the basis of the expectation-maxim...
Imaging thick specimen at a large penetration depth is a challenge in biophysics and material scienc...
A three-dimensional (3-D) point spread function (PSF) model for wide-field fluorescence microscopy, ...
We show a performance analysis of a Depth-Variant Expectation Maximization algorithm previously deve...
We show that the use of multiple depth-variant point-spread functions in 3D fluorescence intensity r...
In three-dimensional microscopy, the image formation process is inherently depth variant (DV) due to...
We show cell images from two different approaches of computational 3D fluorescence imaging integrate...
Three-dimensional (3D) imaging with optical sectioning microscopy uses computational methods to obta...
In three-dimensional (3D) computational imaging for wide-field microscopy, estimation methods that s...
The previously developed depth-variant expectation maximization (DVEM) restoration algorithm for flu...
In three-dimensional fluorescence microscopy, the image formation process is inherently depth varian...
Wavefront encoding (WFE) with different cubic phase mask designs was investigated in engineering 3D ...
A depth-variant (DV) image restoration algorithm for wide field fluorescence microscopy, using an or...
This dissertation proposes a method to restore 3D fluorescence microscopy images obtained from sampl...
Three-dimensional (3D) fluorescence microscopy (FM) is an integral part of biomedical research as it...
We derive an algorithm for maximum-likelihood image estimation on the basis of the expectation-maxim...
Imaging thick specimen at a large penetration depth is a challenge in biophysics and material scienc...
A three-dimensional (3-D) point spread function (PSF) model for wide-field fluorescence microscopy, ...
We show a performance analysis of a Depth-Variant Expectation Maximization algorithm previously deve...
We show that the use of multiple depth-variant point-spread functions in 3D fluorescence intensity r...
In three-dimensional microscopy, the image formation process is inherently depth variant (DV) due to...
We show cell images from two different approaches of computational 3D fluorescence imaging integrate...
Three-dimensional (3D) imaging with optical sectioning microscopy uses computational methods to obta...
In three-dimensional (3D) computational imaging for wide-field microscopy, estimation methods that s...
The previously developed depth-variant expectation maximization (DVEM) restoration algorithm for flu...
In three-dimensional fluorescence microscopy, the image formation process is inherently depth varian...
Wavefront encoding (WFE) with different cubic phase mask designs was investigated in engineering 3D ...
A depth-variant (DV) image restoration algorithm for wide field fluorescence microscopy, using an or...
This dissertation proposes a method to restore 3D fluorescence microscopy images obtained from sampl...
Three-dimensional (3D) fluorescence microscopy (FM) is an integral part of biomedical research as it...
We derive an algorithm for maximum-likelihood image estimation on the basis of the expectation-maxim...
Imaging thick specimen at a large penetration depth is a challenge in biophysics and material scienc...
A three-dimensional (3-D) point spread function (PSF) model for wide-field fluorescence microscopy, ...
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