S. Vasanawala

发表

SPIR-iT : Autocalibrating Parallel Imaging Compressed Sensing

D. Donoho, M. Lustig, J. Pauly, 2008 .

Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction

Arjun D Desai, Mert Pilanci, S. Vasanawala, 2022, MICCAI.

Array Compression for 3 D Cartesian Sampling

J. Pauly, S. Vasanawala, M. Lustig, 2010 .

Practical protocol for lung magnetic resonance imaging and common clinical indications

P. Ciet, S. Vasanawala, K. Sodhi, 2021, Pediatric Radiology.

VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction

Arjun D Desai, J. Pauly, Christopher Ré, 2021, MIDL.

Multicenter Reproducibility of Liver Iron Quantification with 1.5-T and 3.0-T MRI.

S. Reeder, I. Pedrosa, I. Kamel, 2022, Radiology.

Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging

Christopher M. Sandino, M. Lustig, M. Alley, 2022, Bioengineering.

Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised Learning

Christopher M. Sandino, Arjun D Desai, J. Pauly, 2021, 2110.00075.

Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising pdf

John M Pauly, Shreyas Vasanawala, Christopher M. Sandino, 2021, ArXiv.

Quantitative Parametric Mapping of Tissues Properties from Standard Magnetic Resonance Imaging Enabled by Deep Learning

M. Alley, Yajun Ma, E. Chang, 2021, 2108.04912.

An EigenVector Approach to AutoCalibrating Parallel MRI , Where SENSE Meets GRAPPA

M. Elad, J. Pauly, Michael Elad, 2010 .

Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks

David B. Lindell, Dave Van Veen, Arjun D Desai, 2022, ArXiv.

Noise2Recon: Enabling SNR‐robust MRI reconstruction with semi‐supervised and self‐supervised learning

Christopher M. Sandino, Arjun D Desai, J. Pauly, 2023, Magnetic resonance in medicine.

Fast $\ell_1$ -SPIRiT Compressed Sensing Parallel Imaging MRI: Scalable Parallel Implementation and Clinically Feasible Runtime

James Demmel, Kurt Keutzer, Michael Lustig, 2012, IEEE Transactions on Medical Imaging.

K-space refinement in deep learning MR reconstruction via regularizing scan specific SPIRiT-based self consistency

Kanghyun Ryu, Ikbeom Jang, Cagan Alkan, 2021, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction

Christopher M. Sandino, Arjun D Desai, J. Pauly, 2022, ArXiv.

Greedy Learning for Large-Scale Neural MRI Reconstruction

Arjun D Desai, J. Pauly, Mert Pilanci, 2021 .

Evaluation of Patient Positioning to Mitigate RF-induced Heating of Cardiac Implantable Electronic Devices for Pediatric MRI Exams

Daniel B. Ennis, Henry Chubb, Tyler E. Cork, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).