Rethinking data-driven point spread function modeling with a differentiable optical model
Authors: Tobias Liaudat, Jean-Luc Starck, Martin Kilbinger, Pierre-Antoine Frugier Journal: Inverse Problems Year:...
Publications related to signal processing and statistical methods.
Authors: Tobias Liaudat, Jean-Luc Starck, Martin Kilbinger, Pierre-Antoine Frugier Journal: Inverse Problems Year:...
Authors: Utsav Akhaury, Jean-Luc Starck, Pascale Jablonka, Frédéric Courbin, Kevin Michalewicz Journal: A&A Year: 2022 DOI: ...
Deep neural networks have recently been thoroughly investigated as a powerful tool for MRI...
Accelerating MRI scans is one of the principal outstanding problems in the MRI research...
Sparse Blind Source Separation (sBSS) plays a key role in scientific domains as different...
Context. Galaxy imaging surveys observe a vast number of objects that are affected by...
We present a modular cross-domain neural network the XPDNet and its application to the...
Deep neural networks have proven extremely efficient at solving a wide range of inverse...
Sparsity based methods, such as wavelets, have been state-of-the-art for more than 20 years...
The MRI reconstruction field lacked a proper data set that allowed for reproducible...