Contrast-enhanced functional blood volume imaging (CE-fBVI): Enhanced sensitivity for brain activation in humans using the ultrasmall superparamagnetic iron oxide agent ferumoxytol. - Deqiang Qiu; Greg Zaharchuk; Thomas Christen; Wendy W. Ni; Michael E. Moseley (NeuroImage, 2012)

MR vascular fingerprinting: A new approach to compute cerebral blood volume, mean vessel radius, and oxygenation maps in the human brain. - Thomas Christen; N. A. Pannetier; Wendy W. Ni; Deqiang Qiu; Michael E. Moseley; Norbert Schuff; Greg Zaharchuk (NeuroImage, 2014)

Deep Generative Adversarial Networks for Compressed Sensing Automates MRI. - Morteza Mardani; Enhao Gong; Joseph Y. Cheng; Shreyas Vasanawala; Greg Zaharchuk; Marcus T. Alley; Neil Thakur; Song Han 003; William J. Dally; John M. Pauly; Lei Xing 001 (CoRR, 2017)

200x Low-dose PET Reconstruction using Deep Learning. - Junshen Xu; Enhao Gong; John M. Pauly; Greg Zaharchuk (CoRR, 2017)

Erroneous Resting-State fMRI Connectivity Maps Due to Prolonged Arterial Arrival Time and How to Fix Them. - Hesamoddin Jahanian; Thomas Christen; Michael E. Moseley; Greg Zaharchuk (Brain Connect., 2018)

Quantitative susceptibility mapping using deep neural network: QSMnet. - Jaeyeon Yoon; Enhao Gong; Itthi Chatnuntawech; Berkin Bilgic; Jin-Gu Lee; Woojin Jung; Jingyu Ko; Hosan Jung; Kawin Setsompop; Greg Zaharchuk; Eung-Yeop Kim; John M. Pauly; et al. (NeuroImage, 2018)

Task-GAN: Improving Generative Adversarial Network for Image Reconstruction. - Jiahong Ouyang; Guanhua Wang; Enhao Gong; Kevin Chen; John M. Pauly; Greg Zaharchuk (MLMIR@MICCAI, 2019)

Accelerated MRI Reconstruction with Dual-Domain Generative Adversarial Network. - Guanhua Wang; Enhao Gong; Suchandrima Banerjee; John M. Pauly; Greg Zaharchuk (MLMIR@MICCAI, 2019)

Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI. - Endre Grøvik; Darvin Yi; Michael Iv; Elisabeth Tong; Daniel L. Rubin; Greg Zaharchuk (CoRR, 2019)

MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation. - Darvin Yi; Endre Grøvik; Michael Iv; Elisabeth Tong; Kyrre Eeg Emblem; Line Brennhaug Nilsen; Cathrine Saxhaug; Anna Latysheva; Kari Dolven Jacobsen; Åslaug Helland; Greg Zaharchuk; Daniel L. Rubin (CoRR, 2019)

Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study. - Endre Grøvik; Darvin Yi; Michael Iv; Elizabeth Tong; Line Brennhaug Nilsen; Anna Latysheva; Cathrine Saxhaug; Kari Dolven Jacobsen; Åslaug Helland; Kyrre Eeg Emblem; Daniel L. Rubin; Greg Zaharchuk (CoRR, 2019)

Deep Generative Adversarial Neural Networks for Compressive Sensing MRI. - Morteza Mardani; Enhao Gong; Joseph Y. Cheng; Shreyas S. Vasanawala; Greg Zaharchuk; Lei Xing 001; John M. Pauly (IEEE Trans. Medical Imaging, 2019)

Noise-Aware Standard-Dose PET Reconstruction Using General and Adaptive Robust Loss. - Lei Xiang; Long Wang; Enhao Gong; Greg Zaharchuk; Tao Zhang (MLMI@MICCAI, 2020)

Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives. - Darvin Yi; Endre Grøvik; Michael Iv; Elizabeth Tong; Greg Zaharchuk; Daniel L. Rubin (MIDL, 2020)

Deep learning and multi-contrast-based denoising for low-SNR Arterial Spin Labeling (ASL) MRI. - Enhao Gong; Jia Guo; Jiang Liu 014; Audrey P. Fan; John M. Pauly; Greg Zaharchuk (Image Processing, 2020)

Ultra-low-dose 18F-FDG brain PET/MR denoising using deep learning and multi-contrast information. - Junshen Xu; Enhao Gong; Jiahong Ouyang; John M. Pauly; Greg Zaharchuk (Image Processing, 2020)

Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization. - Darvin Yi; Endre Grøvik; Michael Iv; Elizabeth Tong; Greg Zaharchuk; Daniel L. Rubin (CoRR, 2020)

Quantification of brain oxygen extraction and metabolism with [15O]-gas PET: A technical review in the era of PET/MRI. - Audrey P. Fan; Hongyu An; Farshad Moradi; Jarrett Rosenberg; Yosuke Ishii; Tadashi Nariai; Hidehiko Okazawa; Greg Zaharchuk (NeuroImage, 2020)

Deep flow-net for EPI distortion estimation. - Benjamin Zahneisen; Kathrin Bäumler; Greg Zaharchuk; Dominik Fleischmann; Michael Zeineh (NeuroImage, 2020)

Synthesize High-Quality Multi-Contrast Magnetic Resonance Imaging From Multi-Echo Acquisition Using Multi-Task Deep Generative Model. - Guanhua Wang; Enhao Gong; Suchandrima Banerjee; Dann Martin; Elizabeth Tong; Jay Choi; Huijun Chen; Max Wintermark; John M. Pauly; Greg Zaharchuk (IEEE Trans. Medical Imaging, 2020)

Representation Disentanglement for Multi-modal Brain MRI Analysis. - Jiahong Ouyang; Ehsan Adeli 001; Kilian M. Pohl; Qingyu Zhao; Greg Zaharchuk (IPMI, 2021)

Self-supervised Longitudinal Neighbourhood Embedding. - Jiahong Ouyang; Qingyu Zhao; Ehsan Adeli 001; Edith V. Sullivan; Adolf Pfefferbaum; Greg Zaharchuk; Kilian M. Pohl (MICCAI (2), 2021)

Real-Time Video Denoising to Reduce Ionizing Radiation Exposure in Fluoroscopic Imaging. - Dave Van Veen; Ben A. Duffy; Long Wang; Keshav Datta; Tao Zhang; Greg Zaharchuk; Enhao Gong (MLMIR@MICCAI, 2021)

Representation Disentanglement for Multi-modal MR Analysis. - Jiahong Ouyang; Ehsan Adeli 001; Kilian M. Pohl; Qingyu Zhao; Greg Zaharchuk (CoRR, 2021)

Cerebrovascular reactivity measurements using simultaneous 15O-water PET and ASL MRI: Impacts of arterial transit time, labeling efficiency, and hematocrit. - Moss Y. Zhao; Audrey P. Fan; David Yen-Ting Chen; Magdalena J. Sokolska; Jia Guo; Yosuke Ishii; David D. Shin; Mohammad Mehdi Khalighi; Dawn Holley; Kim Halbert; Andrea Otte; Brittney Williams; et al. (NeuroImage, 2021)

Author Correction: Low-count whole-body PET with deep learning in a multicenter and externally validated study. - Akshay S. Chaudhari; Erik Mittra; Guido A. Davidzon; Praveen Gulaka; Harsh Gandhi; Adam Brown; Tao Zhang; Shyam Srinivas; Enhao Gong; Greg Zaharchuk; Hossein Jadvar (npj Digit. Medicine, 2021)

Low-count whole-body PET with deep learning in a multicenter and externally validated study. - Akshay S. Chaudhari; Erik Mittra; Guido A. Davidzon; Praveen Gulaka; Harsh Gandhi; Adam Brown; Tao Zhang; Shyam Srinivas; Enhao Gong; Greg Zaharchuk; Hossein Jadvar (npj Digit. Medicine, 2021)

Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study. - Endre Grøvik; Darvin Yi; Michael Iv; Elizabeth Tong; Line Brennhaug Nilsen; Anna Latysheva; Cathrine Saxhaug; Kari Dolven Jacobsen; Åslaug Helland; Kyrre Eeg Emblem; Daniel L. Rubin; Greg Zaharchuk (npj Digit. Medicine, 2021)

Multi-task Deep Learning for Cerebrovascular Disease Classification and MRI-to-PET Translation. - Ramy Hussein; Moss Y. Zhao; David Shin; Jia Guo; Kevin T. Chen; Rui D. Armindo; Guido A. Davidzon; Michael E. Moseley; Greg Zaharchuk (ICPR, 2022)

Brain MRI-to-PET Synthesis using 3D Convolutional Attention Networks. - Ramy Hussein; David Shin; Moss Y. Zhao; Jia Guo; Guido A. Davidzon; Michael E. Moseley; Greg Zaharchuk (CoRR, 2022)

Non-inferiority of Deep Learning Model to Segment Acute Stroke on Non-contrast CT Compared to Neuroradiologists. - Sophie Ostmeier; Jeremy J. Heit; Brian Axelrod; Li-Jia Li 001; Greg Zaharchuk; Benjamin F. J. Verhaaren; Abdelkader Mahammedi; Soren Christensen; Maarten G. Lansberg (CoRR, 2022)

Self-supervised learning of neighborhood embedding for longitudinal MRI. - Jiahong Ouyang; Qingyu Zhao; Ehsan Adeli 001; Greg Zaharchuk; Kilian M. Pohl (Medical Image Anal., 2022)

Disentangling Normal Aging From Severity of Disease via Weak Supervision on Longitudinal MRI. - Jiahong Ouyang; Qingyu Zhao; Ehsan Adeli 001; Greg Zaharchuk; Kilian M. Pohl (IEEE Trans. Medical Imaging, 2022)

2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data. - Jon André Ottesen; Darvin Yi; Elizabeth Tong; Michael Iv; Anna Latysheva; Cathrine Saxhaug; Kari Dolven Jacobsen; Åslaug Helland; Kyrre Eeg Emblem; Daniel L. Rubin; Atle Bjørnerud; Greg Zaharchuk; et al. (Frontiers Neuroinformatics, 2022)

LSOR: Longitudinally-Consistent Self-Organized Representation Learning. - Jiahong Ouyang; Qingyu Zhao; Ehsan Adeli 001; Wei Peng 009; Greg Zaharchuk; Kilian M. Pohl (MICCAI (1), 2023)

Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model. - Dayang Wang; Srivathsa Pasumarthi; Greg Zaharchuk; Ryan Chamberlain (MICCAI (8), 2023)

Random Expert Sampling for Deep Learning Segmentation of Acute Ischemic Stroke on Non-contrast CT. - Sophie Ostmeier; Brian Axelrod; Benjamin Pulli; Benjamin F. J. Verhaaren; Abdelkader Mahammedi; Yongkai Liu; Christian Federau; Greg Zaharchuk; Jeremy J. Heit (CoRR, 2023)

One Model to Synthesize Them All: Multi-Contrast Multi-Scale Transformer for Missing Data Imputation. - Jiang Liu 014; Srivathsa Pasumarthi; Ben A. Duffy; Enhao Gong; Keshav Datta; Greg Zaharchuk (IEEE Trans. Medical Imaging, 2023)

USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging. - Sophie Ostmeier; Brian Axelrod; Fabian Isensee; Jeroen Bertels; Michael Mlynash; Soren Christensen; Maarten G. Lansberg; Gregory W. Albers; Rajen Sheth; Benjamin F. J. Verhaaren; Abdelkader Mahammedi; Li-Jia Li 001; et al. (Medical Image Anal., 2023)

SOM2LM: Self-Organized Multi-Modal Longitudinal Maps. - Jiahong Ouyang; Qingyu Zhao; Ehsan Adeli 001; Greg Zaharchuk; Kilian M. Pohl (MICCAI (2), 2024)

Turning brain MRI into diagnostic PET: 15O-water PET CBF synthesis from multi-contrast MRI via attention-based encoder-decoder networks. - Ramy Hussein; David D. Shin; Moss Y. Zhao; Jia Guo; Guido A. Davidzon; Gary Steinberg; Michael E. Moseley; Greg Zaharchuk (Medical Image Anal., 2024)

Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment. - Salmonn Talebi; Elizabeth Tong; Anna Li; Ghiam Yamin; Greg Zaharchuk; Mohammad R. K. Mofrad (BMC Medical Informatics Decis. Mak., 2024)

Score-based Generative Diffusion Models to Synthesize Full-dose FDG Brain PET from MRI in Epilepsy Patients. - Jiaqi Wu; Jiahong Ouyang; Farshad Moradi; Mohammad Mehdi Khalighi; Greg Zaharchuk (CoRR, 2025)