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01/25/2023
Data Consistent Deep Rigid MRI Motion Correction
Motion artifacts are a pervasive problem in MRI, leading to misdiagnosis...
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06/22/2022
SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI
Volumetric reconstruction of fetal brains from multiple stacks of MR sli...
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03/10/2022
Autofocusing+: Noise-Resilient Motion Correction in Magnetic Resonance Imaging
Image corruption by motion artifacts is an ingrained problem in Magnetic...
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06/23/2021
STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning
Fetal motion is unpredictable and rapid on the scale of conventional MR ...
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06/23/2021
Deformed2Self: Self-Supervised Denoising for Dynamic Medical Imaging
Image denoising is of great importance for medical imaging system, since...
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04/02/2021
Scan Specific Artifact Reduction in K-space (SPARK) Neural Networks Synergize with Physics-based Reconstruction to Accelerate MRI
Purpose: To develop a scan-specific model that estimates and corrects k-...
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07/16/2020
Enhanced detection of fetal pose in 3D MRI by Deep Reinforcement Learning with physical structure priors on anatomy
Fetal MRI is heavily constrained by unpredictable and substantial fetal ...
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06/23/2020
Semi-Supervised Learning for Fetal Brain MRI Quality Assessment with ROI consistency
Fetal brain MRI is useful for diagnosing brain abnormalities but is chal...
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09/30/2019
Nonlinear Dipole Inversion (NDI) enables Quantitative Susceptibility Mapping (QSM) without parameter tuning
We propose Nonlinear Dipole Inversion (NDI) for high-quality Quantitativ...
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07/10/2019
Fetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network
The performance and diagnostic utility of magnetic resonance imaging (MR...
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03/06/2019
Temporal Registration in Application to In-utero MRI Time Series
We present a robust method to correct for motion in volumetric in-utero ...
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08/12/2016