Unbiased atlas formation via large deformations metric mapping
Unbiased atlas formation via large deformations metric mapping
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DOI：
10.1007/11566489_51
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发表时间：
2005-01-01
期刊：
影响因子：
--
通讯作者：
Joshi, S
中科院分区：
文献类型：
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作者：
Lorenzen, P;Davis, B;Joshi, S
人口地图集的构建是医学图像分析，特别是脑成像的关键问题。将大量图像映射到一个共同的坐标系中，以研究群体内变异性和群体间差异，提供功能部位的体素映射，并通过解剖标签的配准促进组织和对象分割。我们通过大变形度量映射将无偏地图集构造问题表示为在同构空间中的Frechet均值估计。提出了一种新的等速速度场计算方法，并利用熵分析了图谱的稳定性和鲁棒性。我们解决的问题：需要多少图像来建立一个稳定的大脑图谱？
The construction of population atlases is a key issue in medical image analysis, and particularly in brain mapping. Large sets of images are mapped into a common coordinate system to study intrapopulation variability and inter-population differences, to provide voxel-wise mapping of functional sites, and to facilitate tissue and object segmentation via registration of anatomical labels. We formulate the unbiased atlas construction problem as a Frechet mean estimation in the space of diffeomorphisms via large deformations metric mapping. A novel method for computing constant speed velocity fields and an analysis of atlas stability and robustness using entropy are presented. We address the question: how many images are required to build a stable brain atlas?