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A knowledge-based cone-beam x-ray CT algorithm for dynamic volumetric cardiac imaging.

机译:基于知识的锥形束X射线CT算法,用于动态容积心脏成像。

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摘要

With the introduction of spiral/helical multislice CT, medical x-ray CT began a transition into cone-beam geometry. The higher speed, thinner slice, and wider coverage with multislice/cone-beam CT indicate a great potential for dynamic volumetric imaging, with cardiac CT studies being the primary example. Existing ECG-gated cardiac CT algorithms have achieved encouraging results, but they do not utilize any time-varying anatomical information of the heart, and need major improvements to meet critical clinical needs. In this paper, we develop a knowledge-based spiral/helical multislice/cone-beam CT approach for dynamic volumetric cardiac imaging. This approach assumes the relationship between the cardiac status and the ECG signal, such as the volume of the left ventricle as a function of the cardiac phase. Our knowledge-based cardiac CT algorithm is evaluated in numerical simulation and patient studies. In the patient studies, the cardiac status is estimated initially from ECG data and subsequently refined with reconstructed images. Our results demonstrate significant image quality improvements in cardiac CT studies, giving clearly better clarity of the chamber boundaries and vascular structures. In conclusion, this approach seems promising for practical cardiac CT screening and diagnosis.
机译:随着螺旋/螺旋多层CT的引入,医用X射线CT开始向锥束几何过渡。多层/锥束CT的更高速度,更薄的切片以及更宽的覆盖范围表明了动态体积成像的巨大潜力,其中心脏CT研究是主要的例子。现有的ECG门控心脏CT算法取得了令人鼓舞的结果,但它们没有利用任何随时间变化的心脏解剖信息,需要进行重大改进才能满足关键的临床需求。在本文中,我们为动态容积心脏成像开发了一种基于知识的螺旋/螺旋多层/锥束CT方法。该方法假定心脏状态和ECG信号之间的关系(例如,左心室的体积取决于心脏相位)而定。我们基于知识的心脏CT算法在数值模拟和患者研究中得到了评估。在患者研究中,首先从ECG数据估计心脏状态,然后用重建的图像进行完善。我们的结果表明,在心脏CT研究中,图像质量得到了显着改善,使腔室边界和血管结构更加清晰。总之,这种方法对于实际的心脏CT筛查和诊断似乎很有希望。

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