Deconvolution and Denoising for Confocal Microscopy - Modeling in Computational Biology and Biomedicine - page 154

GPU Graphical processing unit

IFFT Inverse Fourier transform

i.i.d. Independent and identically distributed

IU Intensity units

JVC Jansson van Cittert

LSFM Light Sheet based Fluorescence Microscope

LSI Linear shift invariant

MAP Maximum a posteriori

MSE Mean-squared error

MIP Maximum Intensity Projection

ML Maximum likelihood

NA Numerical aperture

NIH National institutes of health

NLS Nonlinear least squares

OME Open microscopy environment

OTF Optical transfer function

PALM Photon activated light microscope

PMT Photomultiplier tube

PN Poisson noise

PSF Point-spread function

PSD Power spectral density

QE Quantum efficiency

RL Richardson-Lucy

RLS Regularized linear least squares

RL-TV Richardson-Lucy Total Variation

RyR Ryanodine

SIM Structured-illumination microscope

SNR Signal-to-noise ratio

STED Stimulated emission depletion

SVI Scientific volume imaging

TM Tikhonov-Miller

TV Total variation

WFM Wide-field microscope

References

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2. D.A. Agard, Y. Hiraoka, P. Shaw, and J.W. Sedat. Fluorescence microscopy in three dimen-
sions. Methods Cell Biol. , 30:353-377, 1989.
3. G. Aubert and P. Kornprobst. Mathematical Problems in Image Processing: Partial Differential
Equations and the Calculus of Variations , volume 147 of Applied Mathematical Sciences .
Springer Verlag, 2006.