no code implementations • 10 May 2023 • Julio A. Oscanoa, Frank Ong, Siddharth S. Iyer, Zhitao Li, Christopher M. Sandino, Batu Ozturkler, Daniel B. Ennis, Mert Pilanci, Shreyas S. Vasanawala
Results: First, we performed ablation experiments to validate the sketching matrix design on both Cartesian and non-Cartesian datasets.
no code implementations • 27 Oct 2022 • Hsiang-Yun Sherry Chien, Hanlin Goh, Christopher M. Sandino, Joseph Y. Cheng
We propose a reconstruction-based self-supervised learning model, the masked auto-encoder for EEG (MAEEG), for learning EEG representations by learning to reconstruct the masked EEG features using a transformer architecture.
no code implementations • 6 Mar 2021 • Ke Wang, Michael Kellman, Christopher M. Sandino, Kevin Zhang, Shreyas S. Vasanawala, Jonathan I. Tamir, Stella X. Yu, Michael Lustig
Deep learning (DL) based unrolled reconstructions have shown state-of-the-art performance for under-sampled magnetic resonance imaging (MRI).
no code implementations • 13 Nov 2019 • Christopher M. Sandino, Peng Lai, Shreyas S. Vasanawala, Joseph Y. Cheng
Feasibility of this approach is demonstrated in reconstructions of prospectively undersampled data which were acquired in a single heartbeat per slice.
no code implementations • 24 Oct 2019 • Mario O. Malavé, Corey A. Baron, Srivathsan P. Koundinyan, Christopher M. Sandino, Frank Ong, Joseph Y. Cheng, Dwight G. Nishimura
Reconstruction with the unrolled network completes in a fraction of the time compared to CPU and GPU implementations of $\textit{l}_{1}$-ESPIRiT (20x and 3x speed increases, respectively).