Automatic 3-D Breath-Hold Related Motion Correction of Dynamic Multislice MRI
Automatic 3-D Breath-Hold Related Motion Correction of Dynamic Multislice MRI
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DOI：
10.1109/tmi.2009.2039145
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发表时间：
2010-03-01
影响因子：
10.6
通讯作者：
Suetens, Paul
中科院分区：
文献类型：
--
作者：
Elen, An;Hermans, Jeroen;Suetens, Paul
磁共振 (MR) 电影图像通常用于临床评估左心室心脏功能。在典型的研究中，会采集多个二维长轴 (LA) 和短轴 (SA) 电影图像，每个图像都处于不同的屏气状态。屏气期间肺容量的差异和患者整体运动会扭曲图像的空间对准，从而使所有图像数据在三个维度上的空间整合变得复杂。我们提出了一种全自动后处理方法来纠正这些切片未对齐。该方法基于自动定义感兴趣区域后相交图像线的强度相似性的约束优化。它同时使用所有视图和所有时间范围。我们的方法对平面内和平面外平移以及完整的 3D 旋转进行建模，可以回顾性地应用，并且不需要心壁分割。该方法在健康志愿者和具有模拟错位的患者数据以及临床多次屏气患者数据上进行了验证。对于模拟数据，可以使用平移校正获得亚像素精度。研究并讨论了旋转校正的可能性和局限性。对于临床多次屏气患者数据集，使用所提出的校正方法，手动 SA 和 LA 轮廓之间的中值差异从 2.83 毫米减少到 1.33 毫米。我们还展示了临床图像数据函数分析校正方法的有用性。位置校正后，考虑到相交切片的新可用补充信息，对相同的临床多次屏气数据集进行重新分割，进一步将中值差异减小至 0.43 mm。这是由于 2D 切片信息集成到 3D 空间中。
Magnetic resonance (MR) cine images are often used to clinically assess left ventricular cardiac function. In a typical study, multiple 2-D long axis (LA) and short axis (SA) cine images are acquired, each in a different breath-hold. Differences in lung volume during breath-hold and overall patient motion distort spatial alignment of the images thus complicating spatial integration of all image data in three dimensions. We present a fully automatic postprocessing approach to correct these slice misalignments. The approach is based on the constrained optimization of the intensity similarity of intersecting image lines after the automatic definition of a region of interest. It uses all views and all time frames simultaneously. Our method models both in-plane and out-of-plane translations and full 3-D rotations, can be applied retrospectively and does not require a cardiac wall segmentation. The method was validated on both healthy volunteer and patient data with simulated misalignments, as well as on clinical multibreath-hold patient data. For the simulated data, subpixel accuracy could be obtained using translational correction. The possibilities and limitations of rotational correction were investigated and discussed. For the clinical multibreath-hold patient data sets, the median discrepancy between manual SA and LA contours was reduced from 2.83 to 1.33 mm using the proposed correction method. We have also shown the usefulness of the correction method for functional analysis on clinical image data. The same clinical multibreath-hold data sets were resegmented after positional correction, taking newly available complementary information of intersecting slices into account, further reducing the median discrepancy to 0.43 mm. This is due to the integration of the 2-D slice information into 3-D space.