基于张量的形态测量法中体积配准算法的比较
COMPARISON OF VOLUMETRIC REGISTRATION ALGORITHMS FOR TENSOR-BASED MORPHOMETRY.
作者信息
Villalon Julio, Joshi Anand A, Toga Arthur W, Thompson Paul M
机构信息
Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA.
出版信息
Proc IEEE Int Symp Biomed Imaging. 2011 Mar-Apr;2011:1536-1541. doi: 10.1109/ISBI.2011.5872694.
Nonlinear registration of brain MRI scans is often used to quantify morphological differences associated with disease or genetic factors. Recently, surface-guided fully 3D volumetric registrations have been developed that combine intensity-guided volume registrations with cortical surface constraints. In this paper, we compare one such algorithm to two popular high-dimensional volumetric registration methods: large-deformation viscous fluid registration, formulated in a Riemannian framework, and the diffeomorphic "Demons" algorithm. We performed an objective morphometric comparison, by using a large MRI dataset from 340 young adult twin subjects to examine 3D patterns of correlations in anatomical volumes. Surface-constrained volume registration gave greater effect sizes for detecting morphometric associations near the cortex, while the other two approaches gave greater effects sizes subcortically. These findings suggest novel ways to combine the advantages of multiple methods in the future.
脑磁共振成像（MRI）扫描的非线性配准常用于量化与疾病或遗传因素相关的形态学差异。最近，已开发出表面引导的全三维体积配准方法，该方法将强度引导的体积配准与皮质表面约束相结合。在本文中，我们将一种这样的算法与两种流行的高维体积配准方法进行比较：在黎曼框架中制定的大变形粘性流体配准，以及微分同胚的“魔鬼”算法。我们通过使用来自340名年轻成年双胞胎受试者的大型MRI数据集来检查解剖体积中的三维相关模式，进行了客观的形态测量比较。表面约束体积配准在检测皮质附近的形态测量关联方面具有更大的效应量，而其他两种方法在皮质下具有更大的效应量。这些发现为未来结合多种方法的优势提供了新途径。
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