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A MACHINE LEARNING MODEL TO ADJUST C-ARM CONE-BEAM COMPUTED TOMOGRAPHY DEVICE TRAJECTORIES
A MACHINE LEARNING MODEL TO ADJUST C-ARM CONE-BEAM COMPUTED TOMOGRAPHY DEVICE TRAJECTORIES
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机译:一种调整C臂锥梁计算机断层扫描装置轨迹的机器学习模型
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摘要
A device may receive an X-ray image captured by a C-arm CBCT device at a particular position defined by a six-degree of freedom pose relative to an anatomy, and may process the X-ray image, with a machine learning model, to determine a predicted quality of next possible X-ray images provided by the C-arm CBCT device. The device may utilize the machine learning model, to identify a particular X-ray image, of the next possible X-ray images, with a greatest predicted quality and to update the six-degree of freedom pose based on the particular X-ray image. The device may provide, to the C-arm CBCT device, data that identifies the updated six-degree of freedom pose to cause the C-arm CBCT device to adjust to a new position based on the updated six-degree of freedom pose.
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