出版物

信息仅用于研究、科学和教育目的。相关出版物中提供的所有声明、数据和结果均应视为用于研究用途。

期刊论文

• Deep Learning Enables 60% Accelerated Volumetric Brain MRI While Preserving Quantitative Performance: A Prospective, Multicenter, Multireader Trial.  AJNR, 2021
• Deep Learning Image Processing Enables 40% Faster Spinal MR Scans Which Match or Exceed Quality of Standard of Care.  Clinical Neuroradiology, 2021
• Validation of Deep Learning–based Augmentation for Reduced 18F FDG Dose for PET/MRI in Children and Young Adults with Lymphoma.  Clinical Neuroradiology, 2021
• Low-count whole-body PET with deep learning in a multicenter and externally validated study.  Nature npj Digital Medicine, 2021
• Deep learning–based methods may minimize GBCA dosage in brain MRI.  European Radiology, 2021

• Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment.  EJNMMI, 2021

• Next generation research applications for hybrid PET/MR and PET/CT imaging using deep learning.  EJNMMI, 2019

• Applications of Deep Learning to Neuro-Imaging Techniques.  Frontiers in Neurology, 2019

• Deep Learning in Neuroradiology:  American Journal of Neuroradiology, 2018
• A generic deep learning model for reduced gadolinium dose in contrast-enhanced brain MRI, Magnetic Resonance in Medicine, 2018
• Deep learning enables reduced gadolinium dose for contrast‐enhanced brain MRI.  Journal of Magnetic Resonance Imaging, 2018

产品研究

• ASNR:  Deep Learning Enables Accurate Quantitative Volumetric Brain MRI with 2x Faster Scan Times.
• ECR:  Evaluating the Capability of Deep Learning (DL) Based Image Processing of Brain MRI to Improve Quality While Reducing Acquisition Times.
• ECR:  Evaluating the Performance of Deep Learning AI (DLAI) to Match Routine Lumbar Spine MRI Image Quality at Highly Reduced Scan Times.
• RSNA:  Accelerating Whole-Body PET Acquisitions Using Deep Learning: External Validation on Foreign Country Data, Quantitative
• RSNA:  Standardized Uptake Value (SUV) Evaluation of 4x Faster PET Scans Enhanced Using Deep Learning
• ISMRM:  Deep Learning Enables Accurate Quantitative Volumetric Brain MRI with 2x Faster Scan.
• ISMRM:  From 2D Thick Slices to 3D Isotropic Volumetric Brain MRI – A Deep Learning Approach.
• ISMRM:  Toward a Site and Scanner-Generic Deep Learning Model for Reduced Gadolinium Dose in Contrast-enhanced Brain MRI
• ISMRM:  Clinical Performance of Reduced Gadolinium Dose for Contrast-Enhanced Brain MRI Using Deep Learning
• NeurIPS: Noise-aware PET image Enhancement with Adaptive Deep Learning.
• 200x Low-dose PET Reconstruction using Deep Learning

深透医疗创始人的其他研究

• Deep Generative Adversarial Neural Networks for Compressive Sensing (GANCS) MRI.
  Mardani, Morteza, Enhao Gong, Joseph Y. Cheng, Shreyas S. Vasanawala, Greg Zaharchuk, Lei Xing, and John M. Pauly.
  IEEE transactions on medical imaging. 2018 Jul 23.
• Quantitative Susceptibility Mapping using Deep Neural Network: QSMnet
  Jaeyeon Yoon*, Enhao Gong*, Itthi Chatnuntawech, Berkin Bilgic, Jingu Lee, Woojin Jung, Jingyu Ko, Hosan Jung, Kawin Setsompop, Greg Zaharchuk, Eung Yeop Kim, John Pauly, Jongho Lee
  NeuroImage 2018 Jun 15.
• Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
  Morteza Mardani, Enhao Gong, Joseph Y. Cheng, Shreyas Vasanawala, Greg Zaharchuk, Marcus Alley, Neil Thakur, Song Han, William Dally, John M. Pauly, Lei Xing
  NIPS Workshop 2017, ISMRM 2017, 2018
• Improved Prediction of the Final Infarct From Acute Stroke Neuroimaging Using Deep Learning
  Yilin Niu*, Enhao Gong*, Junshen Xu, John Pauly, Greg Zaharchuk
  International Stroke Conference (ISC) 2018, ISMRM 2018
• Coil compression for accelerated imaging with Cartesian sampling
  T Zhang, JM Pauly, SS Vasanawala, M Lustig
  Magnetic Resonance in Medicine 2013