抓住
计算机科学
计算机视觉
跟踪(教育)
延迟(音频)
运动(物理)
匹配移动
实时计算
心理学
教育学
电信
程序设计语言
摘要
Purpose To propose a framework called live‐view golden‐angle radial sparse parallel (GRASP) MRI for low‐latency and high‐fidelity real‐time volumetric MRI. Methods Live‐view GRASP MRI has two stages. The first one is called an off‐view stage and the second one is called a live‐view stage. In the off‐view stage, 3D k‐space data and 2D navigators are acquired alternatively using a new navi‐stack‐of‐stars sampling scheme. A 4D motion database is then generated that contains time‐resolved MR images at a sub‐second temporal resolution, and each image is linked to a 2D navigator. In the live‐view stage, only 2D navigators are acquired. At each time point, a live‐view 2D navigator is matched to all the off‐view 2D navigators. A 3D image that is linked to the best‐matched off‐view 2D navigator is then selected for this time point. This framework places the typical acquisition and reconstruction burden of MRI in the off‐view stage, enabling low‐latency real‐time 3D imaging in the live‐view stage. The accuracy of live‐view GRASP MRI and the robustness of 2D navigators for characterizing respiratory variations and/or body movements were assessed. Results Live‐view GRASP MRI can efficiently generate real‐time volumetric images that match well with the ground‐truth references, with an imaging latency below 500 ms. Compared to 1D navigators, 2D navigators enable more reliable characterization of respiratory variations and/or body movements that may occur throughout the two imaging stages. Conclusion Live‐view GRASP MRI represents a novel, accurate, and robust framework for real‐time volumetric imaging, which can potentially be applied for motion adaptive radiotherapy on MRI‐Linac.
科研通智能强力驱动
Strongly Powered by AbleSci AI