no code implementations • 26 Mar 2024 • Amir Aghabiglou, Chung San Chu, Arwa Dabbech, Yves Wiaux
The ``Residual-to-Residual DNN series for high-Dynamic range imaging'' (R2D2) approach was recently introduced for Radio-Interferometric (RI) imaging in astronomy.
no code implementations • 26 Mar 2024 • YiWei Chen, Chao Tang, Amir Aghabiglou, Chung San Chu, Yves Wiaux
We propose a new approach for non-Cartesian magnetic resonance image reconstruction.
no code implementations • 8 Mar 2024 • Amir Aghabiglou, Chung San Chu, Arwa Dabbech, Yves Wiaux
Recent image reconstruction techniques grounded in optimization theory have demonstrated remarkable capability for imaging precision, well beyond CLEAN's capability.
no code implementations • 6 Sep 2023 • Arwa Dabbech, Amir Aghabiglou, Chung San Chu, Yves Wiaux
A novel deep learning paradigm for synthesis imaging by radio interferometry in astronomy was recently proposed, dubbed "Residual-to-Residual DNN series for high-Dynamic range imaging" (R2D2).
no code implementations • 28 Oct 2022 • Amir Aghabiglou, Matthieu Terris, Adrian Jackson, Yves Wiaux
We propose a residual DNN series approach, also interpretable as a learned version of matching pursuit, where the reconstructed image is a sum of residual images progressively increasing the dynamic range, and estimated iteratively by DNNs taking the back-projected data residual of the previous iteration as input.