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Characterization of Regional Pulmonary Mechanics from Serial MRI Data

机译:从串行MRI数据表征区域肺力学

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We describe a method for quantification of lung motion from the registration of successive images in serial MR acquisitions during normal respiration. MR quantification of pulmonary motion enables in vivo assessment of parenchymal mechanics within the lung in order to assist disease diagnosis or treatment monitoring. Specifically, we obtain estimates of pulmonary motion by summing the normalized cross-correlation over the lung images to identify corresponding locations between the images. The normalized correlation is robust to linear intensity distortions in the image acquisition, which may occur as a consequence of changes in average proton density resulting from changes in lung volume during the respiratory cycle. The estimated motions correspond to deformations of an elastic body and reflect to a first order approximation the true physical behavior of lung parenchyma. The method is validated on a serial MRI study of the lung, for which breath-hold images were acquired of a healthy volunteer at different phases of the respiratory cycle.
机译:我们描述了一种从正常呼吸过程中连续MR采集中连续图像的配准量化肺运动的方法。肺运动的MR量化可以对肺内的实质机制进行体内评估,以协助疾病诊断或治疗监测。具体来说,我们通过对肺部图像的归一化互相关求和,以识别图像之间的对应位置,从而获得肺运动的估计值。归一化的相关性对于图像采集中的线性强度畸变具有鲁棒性,线性畸变可能是由于呼吸周期中肺体积的变化而导致的平均质子密度变化而发生的。估计的运动对应于弹性体的变形,并以一阶近似反映肺实质的真实物理行为。该方法在肺部MRI的连续MRI研究中得到验证,为此,在呼吸周期的不同阶段获取了健康志愿者的屏气图像。

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