Images in fluorescence microscopy are inherently blurred due to the limit of diffraction of
light. The purpose of deconvolution microscopy is to compensate numerically for this …

Inverse problems deal with the quest for unknown causes of observed consequences,
based on predictive models, known as the forward models, that associate the former …

The proximal gradient and its variants is one of the most attractive first-order algorithm for
minimizing the sum of two convex functions, with one being nonsmooth. However, it requires …

Far-field optical microscopy using focused light is an important tool in a number of scientific
disciplines including chemical,(bio) physical and biomedical research, particularly with …

Image scanning microscopy (ISM) can improve the effective spatial resolution of confocal
microscopy to its theoretical limit. However, current implementations are not robust or …

Light field microscopy is a new technique for high-speed volumetric imaging of weakly
scattering or fluorescent specimens. It employs an array of microlenses to trade off spatial …

Fourier ring correlation (FRC) has recently gained popularity among fluorescence
microscopists as a straightforward and objective method to measure the effective image …

We provide a lower bound showing that the O (1/k) convergence rate of the NoLips method
(aka Bregman Gradient or Mirror Descent) is optimal for the class of problems satisfying the …

In a stimulated emission depletion (STED) microscope the region in which fluorescence
markers can emit spontaneously shrinks with continued STED beam action after a singular …

We study the problem of minimizing a relatively-smooth convex function using stochastic
Bregman gradient methods. We first prove the convergence of Bregman Stochastic Gradient …