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Evaluation of group-specific whole-brain atlas generation using Volume-based Template Estimation (VTE): application to normal and Alzheimers populations

机译：使用基于体积的模板估计（VTE）评估特定组的全脑图谱生成：应用于正常人群和阿尔茨海默氏症人群

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MRI-based human brain atlases, which serve as a common coordinate system for image analysis, play an increasingly important role in our understanding of brain anatomy, image registration, and segmentation. Study-specific brain atlases are often obtained from one of the subjects in a study or by averaging the images of all participants after linear or non-linear registration. The latter approach has the advantage of providing an unbiased anatomical representation of the study population. But, the image contrast is influenced by both inherent MR contrasts and residual anatomical variability after the registration; in addition, the topology of the brain structures cannot reliably be preserved. In this study, we demonstrated a population-based template-creation approach, which is based on Bayesian template estimation on a diffeomorphic random orbit model. This approach attempts to define a population-representative template without the cross-subject intensity averaging; thus, the topology of the brain structures is preserved. It has been tested for segmented brain structures, such as the hippocampus, but its validity on whole-brain MR images has not been examined. This paper validates and evaluates this atlas generation approach, i.e., Volume-based Template Estimation (VTE). Using datasets from normal subjects and Alzheimer's patients, quantitative measurements of sub-cortical structural volumes, metric distance, displacement vector, and Jacobian were examined to validate the group-averaged shape features of the VTE. In addition to the volume-based quantitative analysis, the preserved brain topology of the VTE allows surface-based analysis within the same atlas framework. This property was demonstrated by analyzing the registration accuracy of the pre- and post-central gyri. The proposed method achieved registration accuracy within 1 mm for these population-preserved cortical structures in an elderly population.
机译：基于MRI的人脑地图集作为图像分析的通用坐标系，在我们对脑解剖结构，图像配准和分割的理解中起着越来越重要的作用。特定于研究的脑图谱通常从研究中的一个受试者中获得，或者通过对线性或非线性配准后所有参与者的图像求平均来获得。后一种方法的优点是提供了研究人群的无偏解剖表示。但是，图像对比度受配准后固有的MR对比度和残留的解剖变异性的影响；另外，大脑结构的拓扑不能可靠地保留。在这项研究中，我们演示了基于人口的模板创建方法，该方法基于微分形随机轨道模型上的贝叶斯模板估计。这种方法试图在不进行跨学科强度平均的情况下定义总体代表模板。因此，大脑结构的拓扑得以保留。它已针对分段的大脑结构（例如海马）进行了测试，但尚未检查其在全脑MR图像上的有效性。本文验证并评估了这种图集生成方法，即基于体积的模板估计（VTE）。使用来自正常受试者和阿尔茨海默氏病患者的数据集，对皮层下结构体积，度量距离，位移向量和雅可比矩阵进行定量测量，以验证VTE的组平均形状特征。除了基于体积的定量分析之外，VTE保留的大脑拓扑还允许在同一图集框架内进行基于表面的分析。通过分析中央前后回旋的配准准确性证明了这一特性。对于老年人群中这些保留人口的皮质结构，所提出的方法实现了1 mm以内的套准精度。

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