Greg Zaharchuk
Orcid: 0000-0001-5781-8848
According to our database1,
Greg Zaharchuk
authored at least 41 papers
between 2012 and 2024.
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Bibliography
2024
Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment.
BMC Medical Informatics Decis. Mak., December, 2024
2023
USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging.
Medical Image Anal., December, 2023
One Model to Synthesize Them All: Multi-Contrast Multi-Scale Transformer for Missing Data Imputation.
IEEE Trans. Medical Imaging, September, 2023
Random Expert Sampling for Deep Learning Segmentation of Acute Ischemic Stroke on Non-contrast CT.
CoRR, 2023
Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
2022
2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data.
Frontiers Neuroinformatics, August, 2022
Disentangling Normal Aging From Severity of Disease via Weak Supervision on Longitudinal MRI.
IEEE Trans. Medical Imaging, 2022
Medical Image Anal., 2022
Non-inferiority of Deep Learning Model to Segment Acute Stroke on Non-contrast CT Compared to Neuroradiologists.
CoRR, 2022
One Model to Synthesize Them All: Multi-contrast Multi-scale Transformer for Missing Data Imputation.
CoRR, 2022
Multi-task Deep Learning for Cerebrovascular Disease Classification and MRI-to-PET Translation.
Proceedings of the 26th International Conference on Pattern Recognition, 2022
2021
Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study.
npj Digit. Medicine, 2021
Low-count whole-body PET with deep learning in a multicenter and externally validated study.
npj Digit. Medicine, 2021
Author Correction: Low-count whole-body PET with deep learning in a multicenter and externally validated study.
npj Digit. Medicine, 2021
Cerebrovascular reactivity measurements using simultaneous <sup>15</sup>O-water PET and ASL MRI: Impacts of arterial transit time, labeling efficiency, and hematocrit.
NeuroImage, 2021
Real-Time Video Denoising to Reduce Ionizing Radiation Exposure in Fluoroscopic Imaging.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the Information Processing in Medical Imaging, 2021
2020
Synthesize High-Quality Multi-Contrast Magnetic Resonance Imaging From Multi-Echo Acquisition Using Multi-Task Deep Generative Model.
IEEE Trans. Medical Imaging, 2020
Quantification of brain oxygen extraction and metabolism with [<sup>15</sup>O]-gas PET: A technical review in the era of PET/MRI.
NeuroImage, 2020
Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization.
CoRR, 2020
Ultra-low-dose 18F-FDG brain PET/MR denoising using deep learning and multi-contrast information.
Proceedings of the Medical Imaging 2020: Image Processing, 2020
Deep learning and multi-contrast-based denoising for low-SNR Arterial Spin Labeling (ASL) MRI.
Proceedings of the Medical Imaging 2020: Image Processing, 2020
Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020
2019
IEEE Trans. Medical Imaging, 2019
Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study.
CoRR, 2019
MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation.
CoRR, 2019
Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI.
CoRR, 2019
Proceedings of the Machine Learning for Medical Image Reconstruction, 2019
Proceedings of the Machine Learning for Medical Image Reconstruction, 2019
2018
NeuroImage, 2018
Erroneous Resting-State fMRI Connectivity Maps Due to Prolonged Arterial Arrival Time and How to Fix Them.
Brain Connect., 2018
2017
CoRR, 2017
2014
MR vascular fingerprinting: A new approach to compute cerebral blood volume, mean vessel radius, and oxygenation maps in the human brain.
NeuroImage, 2014
2012
Contrast-enhanced functional blood volume imaging (CE-fBVI): Enhanced sensitivity for brain activation in humans using the ultrasmall superparamagnetic iron oxide agent ferumoxytol.
NeuroImage, 2012