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用于成对可变形图像配准的空间无关对称数据项

Mid-Space-Independent Symmetric Data Term for Pairwise Deformable Image Registration.

作者信息

Aganj Iman, Iglesias Juan Eugenio, Reuter Martin, Sabuncu Mert Rory, Fischl Bruce

机构信息

Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain,

出版信息

Med Image Comput Comput Assist Interv. 2015 Oct;9350:263-271. doi: 10.1007/978-3-319-24571-3_32. Epub 2015 Nov 20.

Abstract

Aligning a pair of images in a mid-space is a common approach to ensuring that deformable image registration is symmetric - that it does not depend on the arbitrary ordering of the input images. The results are, however, generally dependent on the choice of the mid-space. In particular, the set of possible solutions is typically affected by the constraints that are enforced on the two transformations (that deform the two images), which are to prevent the mid-space from drifting too far from the native image spaces. The use of an implicit atlas has been proposed to define the mid-space for pairwise registration. In this work, we show that by aligning the atlas to each image in the native image space, implicit-atlas-based pairwise registration can be made independent of the mid-space, thereby eliminating the need for anti-drift constraints. We derive a new symmetric cost function that only depends on a single transformation morphing one image to the other, and validate it through diffeomorphic registration experiments on brain magnetic resonance images.

摘要

在中间空间对齐一对图像是确保可变形图像配准对称的常用方法——即它不依赖于输入图像的任意顺序。然而,结果通常取决于中间空间的选择。特别是,可能的解集会受到施加在两个变换(使两个图像变形)上的约束的影响,这些约束是为了防止中间空间偏离原始图像空间太远。有人提出使用隐式图谱来定义用于成对配准的中间空间。在这项工作中,我们表明,通过在原始图像空间中将图谱与每个图像对齐,基于隐式图谱的成对配准可以独立于中间空间,从而消除了对抗漂移约束的需要。我们推导了一个新的对称代价函数,该函数仅依赖于将一个图像变形为另一个图像的单个变换,并通过对脑磁共振图像的微分同胚配准实验对其进行了验证。

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Mid-space-independent deformable image registration.与空间无关的可变形图像配准
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