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用于图像时间序列中变形平行传输的席尔德阶梯。

Schild's ladder for the parallel transport of deformations in time series of images.

作者信息

Lorenzi Marco, Ayache Nicholas, Pennec Xavier

机构信息

Project Team Asclepios, INRIA Sophia Antipolis, France.

出版信息

Inf Process Med Imaging. 2011;22:463-74. doi: 10.1007/978-3-642-22092-0_38.

Abstract

Follow-up imaging studies require the evaluation of the anatomical changes over time for specific clinical groups. The longitudinal changes for a specific subject can be evaluated through the non-rigid registration of successive anatomical images. However, to perform a longitudinal group-wise analysis, the subject-specific longitudinal trajectories of anatomical points need to be transported in a common reference frame. In this work, we propose the Schild's Ladder framework as an effective method to transport longitudinal deformations in time series of images in a common space using diffeomorphic registration. We illustrate the computational advantages and demonstrate the numerical accuracy of this very simple method by comparing with standard methods of transport on simulated images with progressing brain atrophy. Finally, its application to the clinical problem of the measurement of the longitudinal progression in the Alzheimer's disease suggests that an important gain in sensitivity could be expected on group-wise comparisons.

摘要

后续成像研究需要针对特定临床群体评估随时间推移的解剖学变化。特定受试者的纵向变化可通过连续解剖图像的非刚性配准来评估。然而,要进行纵向组分析,解剖学点的受试者特定纵向轨迹需要在一个共同的参考框架中进行传输。在这项工作中,我们提出了希尔德阶梯框架,作为一种有效的方法,通过微分同胚配准在共同空间中传输图像时间序列中的纵向变形。我们通过与具有进行性脑萎缩的模拟图像上的标准传输方法进行比较,说明了该计算方法的优势,并证明了这种非常简单的方法的数值准确性。最后,将其应用于阿尔茨海默病纵向进展测量的临床问题表明,在组间比较中有望获得显著的灵敏度提升。

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