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A generic respiratory motion model for motion correction in PET/CT

机译:用于PET / CT运动校正的通用呼吸运动模型

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Respiratory motion causes different magnitude qualitative and quantitative artefacts in medical imaging and especially in emission tomography. Solutions presented to date include respiratory synchronized PET and CT acquisitions. In order to increase the signal to noise ratio of the synchronized images the use of non-rigid transformations during the reconstruction process accounting for the respiratory motion have been proposed. In the majority of this work the 4D CT images have been used for the derivation of the necessary deformation maps. The objective of this work is to use a global respiratory model to avoid unnecessary 4D CT acquisitions and associated patient dose as well as to improve the temporal resolution of the deformation matrices used in the PET image correction process. The global model is based on principal component analysis (PCA) and can be adapted to a given patient anatomy needing only two static CT images in combination with respiratory synchronised images of the patient surface. The global model was then used to generate n CT images corresponding to a 4D CT temporal resolution (n = 5, 10, 20, 30 and 50) and corresponding deformation matrices. These deformation matrices were then used to correct for the respiratory motion using an elastic transformation correction method during the reconstruction process. NCAT phantom data for two simulated patients and clinical data for six patients (four patients were used for the model creation and two patients for the method validation) were used to determine the optimal number of deformation matrices needed in the reconstruction process.
机译:呼吸运动在医学成像中,尤其是在放射断层扫描中,会引起不同数量级的定性和定量伪像。迄今为止提出的解决方案包括呼吸同步PET和CT采集。为了增加同步图像的信噪比,已经提出在重建过程中考虑呼吸运动的非刚性变换的使用。在大多数这项工作中,已将4D CT图像用于导出必要的变形图。这项工作的目的是使用全局呼吸模型来避免不必要的4D CT采集和相关的患者剂量,以及提高PET图像校正过程中使用的变形矩阵的时间分辨率。全局模型基于主成分分析(PCA),可以适应仅需要两个静态CT图像以及患者表面呼吸同步图像的给定患者解剖结构。然后,使用全局模型生成与4D CT时间分辨率(n = 5、10、20、30和50)相对应的n个CT图像以及相应的变形矩阵。然后在重建过程中使用弹性变形校正方法将这些变形矩阵用于呼吸运动校正。 NCAT幻影数据用于模拟的两名患者和六名患者的临床数据(用于模型创建的四名患者和用于方法验证的两名患者)用于确定重建过程中所需的变形矩阵的最佳数量。

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