Christopher M. Sandino

发表

Accelerating cardiac cine MRI using a deep learning‐based ESPIRiT reconstruction

Peng Lai, Christopher M. Sandino, Shreyas S. Vasanawala, 2019, Magnetic resonance in medicine.

Compressed Sensing: From Research to Clinical Practice With Deep Neural Networks: Shortening Scan Times for Magnetic Resonance Imaging

Morteza Mardani, Joseph Y. Cheng, John M. Pauly, 2020, IEEE Signal Processing Magazine.

Reconstruction of undersampled 3D non‐Cartesian image‐based navigators for coronary MRA using an unrolled deep learning model

Frank Ong, Dwight G. Nishimura, Corey A. Baron, 2019, Magnetic resonance in medicine.

Memory-efficient Learning for High-Dimensional MRI Reconstruction pdf

Michael Lustig, Jonathan I. Tamir, Kevin Zhang, 2021, MICCAI.

Magnetic resonance imaging : Improving medical diagnosis one scan at a time

Christopher M. Sandino, 2013 .

Deep subspace learning for efficient reconstruction of spatiotemporal imaging data

Christopher M. Sandino, S. Vasanawala, Frank Ong, 2021 .

Myocardial T2* mapping: influence of noise on accuracy and precision

Christopher M. Sandino, P. Kellman, A. Arai, 2015, Journal of Cardiovascular Magnetic Resonance.

Near‐silent distortionless DWI using magnetization‐prepared RUFIS

Christopher M. Sandino, Vipul R Sheth, M. Lustig, 2019, Magnetic resonance in medicine.

Rosette Trajectories Enable Ungated, Motion‐Robust, Simultaneous Cardiac and Liver T2* Iron Assessment

Christopher M. Sandino, J. Pauly, S. Vasanawala, 2020, Journal of magnetic resonance imaging : JMRI.

Near‐Silent and Distortion‐Free Diffusion MRI in Pediatric Musculoskeletal Disorders: Comparison With Echo Planar Imaging Diffusion

Christopher M. Sandino, Victoria A. Young, S. Vasanawala, 2020, Journal of magnetic resonance imaging : JMRI.

Prospective Deployment of Deep Learning in MRI: A Framework for Important Considerations, Challenges, and Recommendations for Best Practices

Shreyas S Vasanawala, Matthew P Lungren, Christopher M. Sandino, 2020, Journal of magnetic resonance imaging : JMRI.

Accelerated two‐dimensional phase‐contrast for cardiovascular MRI using deep learning‐based reconstruction with complex difference estimation

Christopher M. Sandino, Matthew J. Middione, S. Vasanawala, 2022, Magnetic resonance in medicine.

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.

Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning pdf

Morteza Mardani, Feiyu Chen, John M. Pauly, 2019, ArXiv.

MAEEG: Masked Auto-encoder for EEG Representation Learning

Christopher M. Sandino, Joseph Y. Cheng, H. Chien, 2022, ArXiv.

SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation

Christopher M. Sandino, Arjun D Desai, B. Hargreaves, 2022, NeurIPS Datasets and Benchmarks.

Free-breathing T2* mapping using respiratory motion corrected averaging

Christopher M. Sandino, P. Kellman, D. Pennell, 2015, Journal of Cardiovascular Magnetic Resonance.

Deep Learning Initialized Compressed Sensing (Deli-CS) in Volumetric Spatio-Temporal Subspace Reconstruction

Christopher M. Sandino, Xiaozhi Cao, C. Liao, 2023, bioRxiv.

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

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

Unsupervised clustering method to convert high-resolution magnetic resonance volumes to three-dimensional acoustic models for full-wave ultrasound simulations

Tao Zhang, Carl D Herickhoff, Kevin Looby, 2019, Journal of medical imaging.

K-means clustering for high-resolution, realistic acoustic maps

Tao Zhang, Jeremy J. Dahl, Kevin Looby, 2018, Medical Imaging.

Coil Sketching for computationally-efficient MR iterative reconstruction

Christopher M. Sandino, Mert Pilanci, S. Vasanawala, 2023, 2305.06482.

Free‐breathing R2∗ mapping of hepatic iron overload in children using 3D multi‐echo UTE cones MRI

Christopher M. Sandino, S. Vasanawala, A. Shimakawa, 2021, Magnetic resonance in medicine.

Diffusion‐weighted double‐echo steady‐state with a three‐dimensional cones trajectory for non‐contrast‐enhanced breast MRI

Christopher M. Sandino, M. Alley, B. Hargreaves, 2020, Journal of magnetic resonance imaging : JMRI.

Free-breathing Accelerated Cardiac MRI Using Deep Learning: Validation in Children and Young Adults.

Christopher M. Sandino, S. Vasanawala, A. Kino, 2021, Radiology.

Upstream Machine Learning in Radiology.

Christopher M. Sandino, Adam S. Wang, Elizabeth K. Cole, 2021, Radiologic clinics of North America.

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.

Accelerating cardiac cine MRI beyond compressed sensing using DL-ESPIRiT pdf

Peng Lai, Christopher M. Sandino, Shreyas S. Vasanawala, 2019, ArXiv.

Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges

Ukash Nakarmi, John M. Pauly, Shreyas Vasanawala, 2019, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction

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

Coil Sketching for computationally-efficient MR iterative reconstruction

Christopher M. Sandino, Mert Pilanci, S. Vasanawala, 2023, 2305.06482.