Hui Xue

Principal Researcher

Publications

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- High-resolution ultra-low-field MRI with SNRAware denoising
  
  T. Guallart-Naval, Hui Xue, J. M. Algar'in, Eli G. Castanon, J. Conejero, F. Galve, M. Nassejje, John Stairs, L. Vega-Cid, Michael Hansen, Joseba Alonso
  
  April 2026
  
  Publication
- SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation
  
  Hui Xue, Sarah M. Hooper, Iain Pierce, Rhodri H. Davies, John Stairs, Joseph Naegele, A. Campbell-Washburn, Charlotte Manisty, James C. Moon, T. Treibel, Peter Kellman, Michael Hansen
  
  Radiology: Artificial Intelligence | October 2025, Vol 7(6)
  
  Publication Preprint Project
- Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging
  
  Hui Xue, Sarah M. Hooper, Rhodri H. Davies, T. Treibel, Iain Pierce, John Stairs, Joseph Naegele, Charlotte Manisty, James C. Moon, A. Campbell-Washburn, Peter Kellman, Michael Hansen
  
  April 2025
  
  Publication Project
- Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
  
  Hui Xue
  
  Scientific Reports | March 2025, Vol 14
  
  Publication
- A Study on Context Length and Efficient Transformers for Biomedical Image Analysis
  
  Sarah Hooper, Hui Xue
  
  Machine Learning for Health (ML4H) 2024 | November 2024
  
  Author's Version
- Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
  
  Hui Xue
  
  ISMRM | May 2024
  
  Publication Publication
- Inline AI: Open-source Deep Learning Inference for Cardiac MR
  
  Hui Xue
  
  April 2024
  
  Publication Publication
- Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR
  
  Hui Xue
  
  Journal of Cardiovascular Magnetic Resonance | February 2024, Vol 26
  
  Publication Publication

- High-resolution ultra-low-field MRI with SNRAware denoising
  
  T. Guallart-Naval, Hui Xue, J. M. Algar'in, Eli G. Castanon, J. Conejero, F. Galve, M. Nassejje, John Stairs, L. Vega-Cid, Michael Hansen, Joseba Alonso
  
  April 2026
  
  Publication
- SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation
  
  Hui Xue, Sarah M. Hooper, Iain Pierce, Rhodri H. Davies, John Stairs, Joseph Naegele, A. Campbell-Washburn, Charlotte Manisty, James C. Moon, T. Treibel, Peter Kellman, Michael Hansen
  
  Radiology: Artificial Intelligence | October 2025, Vol 7(6)
  
  Publication Preprint Project
- Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging
  
  Hui Xue, Sarah M. Hooper, Rhodri H. Davies, T. Treibel, Iain Pierce, John Stairs, Joseph Naegele, Charlotte Manisty, James C. Moon, A. Campbell-Washburn, Peter Kellman, Michael Hansen
  
  April 2025
  
  Publication Project
- Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
  
  Hui Xue
  
  Scientific Reports | March 2025, Vol 14
  
  Publication
- A Study on Context Length and Efficient Transformers for Biomedical Image Analysis
  
  Sarah Hooper, Hui Xue
  
  Machine Learning for Health (ML4H) 2024 | November 2024
  
  Author's Version
- Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
  
  Hui Xue
  
  ISMRM | May 2024
  
  Publication Publication
- Inline AI: Open-source Deep Learning Inference for Cardiac MR
  
  Hui Xue
  
  April 2024
  
  Publication Publication
- Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR
  
  Hui Xue
  
  Journal of Cardiovascular Magnetic Resonance | February 2024, Vol 26
  
  Publication Publication
- High-resolution ultra-low-field MRI with SNRAware denoising
  
  T. Guallart-Naval, Hui Xue, J. M. Algar'in, Eli G. Castanon, J. Conejero, F. Galve, M. Nassejje, John Stairs, L. Vega-Cid, Michael Hansen, Joseba Alonso
  
  April 2026
  
  Publication
- SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation
  
  Hui Xue, Sarah M. Hooper, Iain Pierce, Rhodri H. Davies, John Stairs, Joseph Naegele, A. Campbell-Washburn, Charlotte Manisty, James C. Moon, T. Treibel, Peter Kellman, Michael Hansen
  
  Radiology: Artificial Intelligence | October 2025, Vol 7(6)
  
  Publication Preprint Project
- Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging
  
  Hui Xue, Sarah M. Hooper, Rhodri H. Davies, T. Treibel, Iain Pierce, John Stairs, Joseph Naegele, Charlotte Manisty, James C. Moon, A. Campbell-Washburn, Peter Kellman, Michael Hansen
  
  April 2025
  
  Publication Project
- A Study on Context Length and Efficient Transformers for Biomedical Image Analysis
  
  Sarah Hooper, Hui Xue
  
  Machine Learning for Health (ML4H) 2024 | November 2024
  
  Author's Version
- Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
  
  Hui Xue
  
  ISMRM | May 2024
  
  Publication Publication
- Inline AI: Open-source Deep Learning Inference for Cardiac MR
  
  Hui Xue
  
  April 2024
  
  Publication Publication
- Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR
  
  Hui Xue
  
  Journal of Cardiovascular Magnetic Resonance | February 2024, Vol 26
  
  Publication Publication
- SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation
  
  Hui Xue, Sarah M. Hooper, Iain Pierce, Rhodri H. Davies, John Stairs, Joseph Naegele, A. Campbell-Washburn, Charlotte Manisty, James C. Moon, T. Treibel, Peter Kellman, Michael Hansen
  
  Radiology: Artificial Intelligence | October 2025, Vol 7(6)
  
  Publication Preprint Project
- Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging
  
  Hui Xue, Sarah M. Hooper, Rhodri H. Davies, T. Treibel, Iain Pierce, John Stairs, Joseph Naegele, Charlotte Manisty, James C. Moon, A. Campbell-Washburn, Peter Kellman, Michael Hansen
  
  April 2025
  
  Publication Project
- Inline AI: Open-source Deep Learning Inference for Cardiac MR
  
  Hui Xue
  
  April 2024
  
  Publication Publication

- High-resolution ultra-low-field MRI with SNRAware denoising
  
  T. Guallart-Naval, Hui Xue, J. M. Algar'in, Eli G. Castanon, J. Conejero, F. Galve, M. Nassejje, John Stairs, L. Vega-Cid, Michael Hansen, Joseba Alonso
  
  April 2026
  
  Publication
- Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging
  
  Hui Xue, Sarah M. Hooper, Rhodri H. Davies, T. Treibel, Iain Pierce, John Stairs, Joseph Naegele, Charlotte Manisty, James C. Moon, A. Campbell-Washburn, Peter Kellman, Michael Hansen
  
  April 2025
  
  Publication Project
- SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation
  
  Hui Xue, Sarah M. Hooper, Iain Pierce, Rhodri H. Davies, John Stairs, Joseph Naegele, A. Campbell-Washburn, Charlotte Manisty, James C. Moon, T. Treibel, Peter Kellman, Michael Hansen
  
  Radiology: Artificial Intelligence | October 2025, Vol 7(6)
  
  Publication Preprint Project
- Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
  
  Hui Xue
  
  Scientific Reports | March 2025, Vol 14
  
  Publication
- Inline AI: Open-source Deep Learning Inference for Cardiac MR
  
  Hui Xue
  
  April 2024
  
  Publication Publication
- Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR
  
  Hui Xue
  
  Journal of Cardiovascular Magnetic Resonance | February 2024, Vol 26
  
  Publication Publication
- A Study on Context Length and Efficient Transformers for Biomedical Image Analysis
  
  Sarah Hooper, Hui Xue
  
  Machine Learning for Health (ML4H) 2024 | November 2024
  
  Author's Version
- Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
  
  Hui Xue
  
  ISMRM | May 2024
  
  Publication Publication

Hui Xue

Publications

High-resolution ultra-low-field MRI with SNRAware denoising

SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation

Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging

Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation

A Study on Context Length and Efficient Transformers for Biomedical Image Analysis

Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy

Inline AI: Open-source Deep Learning Inference for Cardiac MR

Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR

High-resolution ultra-low-field MRI with SNRAware denoising

SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation

Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging

Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation

A Study on Context Length and Efficient Transformers for Biomedical Image Analysis

Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy

Inline AI: Open-source Deep Learning Inference for Cardiac MR

Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR

High-resolution ultra-low-field MRI with SNRAware denoising

SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation

Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging

A Study on Context Length and Efficient Transformers for Biomedical Image Analysis

Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy

Inline AI: Open-source Deep Learning Inference for Cardiac MR

Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR

SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation

Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging

Inline AI: Open-source Deep Learning Inference for Cardiac MR

High-resolution ultra-low-field MRI with SNRAware denoising

Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR<<1 Imaging

SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-factor Map Augmentation

Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation

Inline AI: Open-source Deep Learning Inference for Cardiac MR

Characterizing the Signal-to-noise Ratio and Spatio-temporal Resolution of an Imaging Transformer Model for CMR

A Study on Context Length and Efficient Transformers for Biomedical Image Analysis

Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy

Contact Hui Xue

Microsoft Health Futures