Christophe Schülke

TL;DR: This paper shows that the transmission matrix of a highly scattering medium can still be retrieved, through signal processing techniques of phase retrieval, and is experimentally validated on three criteria : quality of prediction, distribution of singular values, and quality of focusing.

TL;DR: In this paper, the phase of the transmission matrix of a highly scattering medium is estimated using phase retrieval techniques using the optical setup of a digital micromirror device (DMD).

TL;DR: It is shown empirically that after proper randomization, the structure of the operators does not significantly affect the performances of the solver, and for some specially designed spatially coupled operators, this allows a computationally fast and memory efficient reconstruction in compressed sensing up to the information-theoretical limit.

TL;DR: In this article, the behavior of approximate message-passing (AMP), a solver for linear sparse estimation problems such as compressed sensing, when the i.i.d matrices, for which it has been specifically designed, are replaced by structured operators, such as Fourier and Hadamard ones, was investigated.

TL;DR: A novel deep neural network is developed to refine and correct prior reconstruction assumptions given the training data to accelerate MR acquisition and demonstrates the superior performance and wide applicability of the method.