Michael Hansen

Director, 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
- Analog optical computer for AI inference and combinatorial optimization
  
  Kirill P. Kalinin, Jannes Gladrow, Jiaqi Chu, James H. Clegg, Daniel Cletheroe, Douglas J. Kelly, Babak Rahmani, Grace Brennan, Burcu Canakci, Fabian Falck, Michael Hansen, Jim Kleewein, Heiner Kremer, Greg O’Shea, Lucinda Pickup, Saravan Rajmohan, Ant Rowstron, Victor Ruehle, Lee Braine, Shrirang Khedekar, Natalia G. Berloff, Christos Gkantsidis, Francesca Parmigiani, Hitesh Ballani
  
  Nature | September 2025
  
  Publication 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
- End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction
  
  Ruiyang Zhao, Yuxin Zhang, Matthew P. Lungren, Michael Hansen
  
  arXiv: Computer Vision and Pattern Recognition | September 2021, (arXiv:2109.11524)
  
  Publication
- fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data
  
  Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren
  
  arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812
  
  Publication Github Project

- 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
- Analog optical computer for AI inference and combinatorial optimization
  
  Kirill P. Kalinin, Jannes Gladrow, Jiaqi Chu, James H. Clegg, Daniel Cletheroe, Douglas J. Kelly, Babak Rahmani, Grace Brennan, Burcu Canakci, Fabian Falck, Michael Hansen, Jim Kleewein, Heiner Kremer, Greg O’Shea, Lucinda Pickup, Saravan Rajmohan, Ant Rowstron, Victor Ruehle, Lee Braine, Shrirang Khedekar, Natalia G. Berloff, Christos Gkantsidis, Francesca Parmigiani, Hitesh Ballani
  
  Nature | September 2025
  
  Publication 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
- End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction
  
  Ruiyang Zhao, Yuxin Zhang, Matthew P. Lungren, Michael Hansen
  
  arXiv: Computer Vision and Pattern Recognition | September 2021, (arXiv:2109.11524)
  
  Publication
- fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data
  
  Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren
  
  arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812
  
  Publication Github Project
- 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
- fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data
  
  Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren
  
  arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812
  
  Publication Github 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
- 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

- 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
- Analog optical computer for AI inference and combinatorial optimization
  
  Kirill P. Kalinin, Jannes Gladrow, Jiaqi Chu, James H. Clegg, Daniel Cletheroe, Douglas J. Kelly, Babak Rahmani, Grace Brennan, Burcu Canakci, Fabian Falck, Michael Hansen, Jim Kleewein, Heiner Kremer, Greg O’Shea, Lucinda Pickup, Saravan Rajmohan, Ant Rowstron, Victor Ruehle, Lee Braine, Shrirang Khedekar, Natalia G. Berloff, Christos Gkantsidis, Francesca Parmigiani, Hitesh Ballani
  
  Nature | September 2025
  
  Publication Project
- End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction
  
  Ruiyang Zhao, Yuxin Zhang, Matthew P. Lungren, Michael Hansen
  
  arXiv: Computer Vision and Pattern Recognition | September 2021, (arXiv:2109.11524)
  
  Publication
- fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data
  
  Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael Hansen, Matthew P. Lungren
  
  arXiv: Computer Vision and Pattern Recognition | September 2021, Vol arXiv:2109.03812
  
  Publication Github Project

Michael Hansen

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

Analog optical computer for AI inference and combinatorial optimization

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

End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

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

Analog optical computer for AI inference and combinatorial optimization

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

End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

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

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

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

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

Analog optical computer for AI inference and combinatorial optimization

End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data