Image registration framework for large-scale longitudinal MRI data sets: strategy and validation
Image registration framework for large-scale longitudinal MRI data sets: strategy and validation
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DOI：
10.1016/j.mri.2007.03.004
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发表时间：
2007-07-01
影响因子：
2.5
通讯作者：
Guttmann, Charles R. G.
中科院分区：
文献类型：
--
作者：
Csapo, Istvan;Holland, Christopher M.;Guttmann, Charles R. G.
先进的磁共振成像(MRI)研究通常需要将大量图像转换到公共空间。计算将每个图像相互关联的变换并按需将它们应用于图像在理论上是可能的；然而，这在计算上可能是不可行的。因此，将每个图像仅与一个其他图像关联，然后将这些变换链接在一起以关联数据库中的任何两个图像，可能是一种有效的替代方案。评估了图像配准的可行性和有效性，通过连接预计算变换，将个体内MR图像相互对应起来进行纵向分析。使用了10名多发性硬化症患者的纵向数据集，这些患者进行了9次连续的双回波自旋回波，1.5-T磁共振扫描。对象内配准是在连续图像之间逐步进行的，并从每个时间点直接到基线。通过比较得到的变换图像(使用皮尔逊相关系数)，将连续变换连接起来并与直接配准进行比较。混杂的变量，如扫描间隔时间、脑萎缩和病变负荷的变化进行了评估。我们发现，用直接变换和级联变换重采样的图像高度相关，并且两种方法之间没有显著差异。脑实质分数(脑萎缩的衡量标准)的差异与重新采样图像的一致性显示出显著的负相关。结果表明，将两幅图像连接在一起的多个变换得到的结果与直接配准的结果几乎相同，因此，该方法是有用和有效的。(C)2007 Elsevier Inc.保留所有权利。
Advanced magnetic resonance imaging (MRI) studies often require the transformation of large numbers of images into a common space. Calculating transformations that relate each image to every other and applying them to the images on demand are theoretically possible; however, these can be computationally prohibitive. Therefore, relating each image to only one other image, then linking those transforms together to relate any two images in the database, may be an efficient alternative. Evaluated were the feasibility and validity of image registration to bring intraindividual MR images into mutual correspondence for longitudinal analysis through the concatenation of precomputed transforms. A longitudinal data set of 10 multiple sclerosis patients with nine serial dual-echo spin-echo, 1.5-T MR] scans was used. Intrasubject registrations were performed stepwise between consecutive images and direct from each time point to the baseline. Consecutive transforms were concatenated and evaluated against direct registrations by comparing the resulting transformed images (using Pearson correlation coefficient). Confounding variables such as time between scans, brain atrophy, and change in lesion load were evaluated. We found the images resampled with the direct and the concatenated transforms to be highly correlated, and there was no significant difference between methods. Differences in brain parenchymal fraction (a measure of brain atrophy) showed significant inverse correlation with the correspondence of the resampled images. Results indicate that concatenating multiple transforms that link two images together produces near-identical results to that of direct registration; thus, this method is both useful and valid. (c) 2007 Elsevier Inc. All rights reserved.