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IEEE Transactions on Medical Imaging
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February 26, 2019
Understanding the Combined Effect of k -Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions
Christiaan C Stolk, Alessandro Sbrizzi
IEEE Transactions on Medical Imaging
|
August 4, 2020
Accelerated MR-STAT Reconstructions Using Sparse Hessian Approximations
Oscar van der Heide, Alessandro Sbrizzi, Cornelis A T van den Berg
Magnetic Resonance in Medicine
|
March 5, 2024
GPU-accelerated Bloch simulations and MR-STAT reconstructions using the Julia programming language
Oscar van der Heide, Cornelis A T van den Berg, Alessandro Sbrizzi
Magnetic Resonance in Medicine
|
February 25, 2018
Whole-brain 3D FLAIR at 7T using direct signal control
Arian Beqiri, Hans Hoogduin, Alessandro Sbrizzi, et al.
Magnetic Resonance Imaging
|
January 28, 2023
Cartesian vs radial MR-STAT: An efficiency and robustness study
Oscar van der Heide, Alessandro Sbrizzi, Cornelis A T van den Berg
Medical Image Analysis
|
June 10, 2022
⊥-loss: A symmetric loss function for magnetic resonance imaging reconstruction and image registration with deep learning
Maarten L Terpstra, Matteo Maspero, Alessandro Sbrizzi, et al.
Magnetic Resonance in Medicine
|
November 10, 2020
Nonrigid 3D motion estimation at high temporal resolution from prospectively undersampled k-space data using low-rank MR-MOTUS
Niek R F Huttinga, Tom Bruijnen, Cornelis A T van den Berg, et al.
IEEE Transactions on Medical Imaging
|
September 14, 2021
Real-Time Non-Rigid 3D Respiratory Motion Estimation for MR-Guided Radiotherapy Using MR-MOTUS
Niek R F Huttinga, Tom Bruijnen, Cornelis A T Van Den Berg, et al.
Medical Image Analysis
|
May 28, 2023
Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy
Niek R F Huttinga, Tom Bruijnen, Cornelis A T van den Berg, et al.
NMR in Biomedicine
|
May 5, 2021
Fast and accurate modeling of transient-state, gradient-spoiled sequences by recurrent neural networks
Hongyan Liu, Oscar van der Heide, Cornelis A T van den Berg, et al.
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Showing results (1-10 of 52) with videos related to
Sort By:
Page
of 6
IEEE Transactions on Medical Imaging
|
February 26, 2019
Understanding the Combined Effect of k -Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions
Christiaan C Stolk, Alessandro Sbrizzi
IEEE Transactions on Medical Imaging
|
August 4, 2020
Accelerated MR-STAT Reconstructions Using Sparse Hessian Approximations
Oscar van der Heide, Alessandro Sbrizzi, Cornelis A T van den Berg
Magnetic Resonance in Medicine
|
March 5, 2024
GPU-accelerated Bloch simulations and MR-STAT reconstructions using the Julia programming language
Oscar van der Heide, Cornelis A T van den Berg, Alessandro Sbrizzi
Magnetic Resonance in Medicine
|
February 25, 2018
Whole-brain 3D FLAIR at 7T using direct signal control
Arian Beqiri, Hans Hoogduin, Alessandro Sbrizzi, et al.
Magnetic Resonance Imaging
|
January 28, 2023
Cartesian vs radial MR-STAT: An efficiency and robustness study
Oscar van der Heide, Alessandro Sbrizzi, Cornelis A T van den Berg
Medical Image Analysis
|
June 10, 2022
⊥-loss: A symmetric loss function for magnetic resonance imaging reconstruction and image registration with deep learning
Maarten L Terpstra, Matteo Maspero, Alessandro Sbrizzi, et al.
Magnetic Resonance in Medicine
|
November 10, 2020
Nonrigid 3D motion estimation at high temporal resolution from prospectively undersampled k-space data using low-rank MR-MOTUS
Niek R F Huttinga, Tom Bruijnen, Cornelis A T van den Berg, et al.
IEEE Transactions on Medical Imaging
|
September 14, 2021
Real-Time Non-Rigid 3D Respiratory Motion Estimation for MR-Guided Radiotherapy Using MR-MOTUS
Niek R F Huttinga, Tom Bruijnen, Cornelis A T Van Den Berg, et al.
Medical Image Analysis
|
May 28, 2023
Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy
Niek R F Huttinga, Tom Bruijnen, Cornelis A T van den Berg, et al.
NMR in Biomedicine
|
May 5, 2021
Fast and accurate modeling of transient-state, gradient-spoiled sequences by recurrent neural networks
Hongyan Liu, Oscar van der Heide, Cornelis A T van den Berg, et al.
Page
of 6