MRI reconstruction using real-time motion tracking: A simulation study
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Using a simulated MRI scanner, we compare the different ways to use the motion-tracking data (both retrospectively and prospectively) and compare the ...
Abstract—Previous efforts to compensate for patient motion in. MRI invariably assume that the patient is motionless for some part of the scan.
Using a simulated MRI scanner, we compare the different ways to use the motion-tracking data (both retrospectively and prospectively) and compare the ...
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In this paper we introduce a novel platform-independent motion-robust MRI technique based on prospective real-time motion tracking through a miniature magnetic ...
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This is achieved by integrating a motion module into the deep learning-based MRI reconstruction process, enabling real-time detection and correction of motion.
Motion estimation from severely downsampled 4D-MRI is essential for real-time imaging and tumor tracking. This simulation study developed a novel deep learning ...
Dec 12, 2023 · Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy. Phys ...
May 31, 2024 · This is achieved by integrating a motion module into the deep learning-based MRI reconstruction process, enabling real-time detection and ...
Deep learning‐based image reconstruction and motion estimation from undersampled radial k‐space for real‐time MRI‐guided radiotherapy. Phys Med Biol. 2020 ...
Jan 16, 2023 · Here, we test the suitability of deep-learning-based image reconstruction for real-time tracking applications on MRI-Linacs. Methods. We use ...