1 code implementation • 23 Nov 2023 • Martin Schilling, Christina Unterberg-Buchwald, Joachim Lotz, Martin Uecker
In this work, accuracy of deep learning methods is assessed for volumetric analysis (via segmentation) of the left ventricle in real-time free-breathing CMR at rest and under exercise stress.
2 code implementations • 4 Aug 2023 • GuanXiong Luo, Xiaoqing Wang, Mortiz Blumenthal, Martin Schilling, Erik Hans Ulrich Rauf, Raviteja Kotikalapudi, Niels Focke, Martin Uecker
Purpose: In this work, we present a workflow to construct generic and robust generative image priors from magnitude-only images.
1 code implementation • 28 Feb 2022 • Moritz Blumenthal, GuanXiong Luo, Martin Schilling, H. Christian M. Holme, Martin Uecker
Conclusion: By integrating non-linear operators and neural networks into BART, we provide a general framework for deep-learning-based reconstruction in MRI.
1 code implementation • 3 Feb 2022 • GuanXiong Luo, Moritz Blumenthal, Martin Heide, Martin Uecker
We introduce a framework that enables efficient sampling from learned probability distributions for MRI reconstruction.
1 code implementation • 3 Oct 2020 • Xiaoqing Wang, Zhengguo Tan, Nick Scholand, Volkert Roeloffs, Martin Uecker
Conventional Magnetic Resonance Imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems.
no code implementations • 10 Aug 2020 • Oliver Maier, Steven H. Baete, Alexander Fyrdahl, Kerstin Hammernik, Seb Harrevelt, Lars Kasper, Agah Karakuzu, Michael Loecher, Franz Patzig, Ye Tian, Ke Wang, Daniel Gallichan, Martin Uecker, Florian Knoll
The reference implementations were in good agreement, both visually and in terms of image similarity metrics.
1 code implementation • 23 Sep 2019 • Xiaoqing Wang, Sebastian Rosenzweig, Nick Scholand, H. Christian M. Holme, Martin Uecker
Validations of the proposed method are performed for a phantom and for the human brain and liver in six healthy adult subjects.
Medical Physics Image and Video Processing
1 code implementation • 25 Feb 2019 • Frank Ong, Martin Uecker, Michael Lustig
We propose a k-space preconditioning formulation for accelerating the convergence of iterative Magnetic Resonance Imaging (MRI) reconstructions from non-uniformly sampled k-space data.
Medical Physics
1 code implementation • 21 Dec 2018 • Sebastian Rosenzweig, Nick Scholand, H. Christian M. Holme, Martin Uecker
Cardiac Magnetic Resonance Imaging (MRI) is time-consuming and error-prone.
Medical Physics
1 code implementation • 11 May 2018 • Sebastian Rosenzweig, H. Christian M. Holme, Martin Uecker
Using the proposed method (RING), these parameters can be obtained using a least-squares fit and utilized for the correction of gradient delays.
Medical Physics
1 code implementation • 29 Jun 2017 • H. Christian M. Holme, Sebastian Rosenzweig, Frank Ong, Robin N. Wilke, Michael Lustig, Martin Uecker
Robustness against data inconsistencies, imaging artifacts and acquisition speed are crucial factors limiting the possible range of applications for magnetic resonance imaging (MRI).
Medical Physics
1 code implementation • 11 May 2017 • Sebastian Rosenzweig, H. Christian M. Holme, Robin N. Wilke, Dirk Voit, Jens Frahm, Martin Uecker
Purpose: The development of a calibrationless parallel imaging method for accelerated simultaneous multi-slice (SMS) MRI based on Regularized Nonlinear Inversion (NLINV), evaluated using Cartesian and radial FLASH.
Medical Physics
1 code implementation • 17 Jul 2015 • Martin Uecker, Michael Lustig
Based on this method, a new post-processing step is proposed for the explicit computation of coil sensitivities that include the absolute phase of the image.
no code implementations • 25 Jan 2015 • Martin Uecker
The main disadvantage of Magnetic Resonance Imaging (MRI) are its long scan times and, in consequence, its sensitivity to motion.