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Nonrigid Motion Compensation of Free Breathing Acquired Myocardial Perfusion Data

机译:自由呼吸获得的心肌灌注数据的非刚性运动补偿

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摘要

In this work, we present a novel method to compensate the movement in images acquired during free breathing using first-pass gadolinium enhanced, myocardial perfusion magnetic resonance imaging (MRI). First, we use independent component analysis (ICA) to identify the optimal number of independent components (ICs) that separate the breathing motion from the intensity change induced by the contrast agent. Then, synthetic images are created by recombining the ICs, but other then in previously published work (Milles et al. 2008), we omit the component related to motion, and therefore, the resulting reference image series is free of motion. Motion compensation is then achieved by using a multi-pass non-rigid image registration scheme. We tested our method on 15 distinct image series (5 patients) consisting of 58 images each and we validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration. The average correlation to the manually obtained curves before registration 0:89 0:11 was increased to 0:98 0:02
机译:在这项工作中,我们提出了一种新颖的方法,以补偿使用第一遍enhanced增强的心肌灌注磁共振成像(MRI)在自由呼吸期间获得的图像中的运动。首先,我们使用独立成分分析(ICA)来确定将呼吸运动与造影剂引起的强度变化区分开来的独立成分(IC)的最佳数量。然后,通过重新组合IC来创建合成图像,但是在以前发表的工作中(Milles等,2008),我们省略了与运动有关的分量,因此,生成的参考图像系列没有运动。然后,通过使用多遍非刚性图像配准方案来实现运动补偿。我们在15个不同的图像系列(5个患者)中测试了我们的方法,每个图像系列由58个图像组成,并且我们通过将手动跟踪的心肌切片的强度轮廓与配准前后自动生成的强度轮廓进行了比较来验证了我们的方法。与注册0:89 0:11之前手动获得的曲线的平均相关性增加到0:98 0:02

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