In the context of MR-guided radiotherapy, 4D-MRI is of particular interest for lung and abdominal cancer treatment, as it enables quantifying the extent of respiratory motion at the time of treatment, facilitating time-efficient midposition treatments. To reduce long reconstruction times of iterative compressed sensing-based reconstructions involving algorithms, such as XD-GRASP, we used a fast C++ implementation. We evaluated the impact of using overlapping respiratory bins and different self-gating signals on image quality and reconstruction time in multiple patients with and without abdominal compression belts.
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