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通过大变形度量映射实现无偏图谱构建。

Unbiased atlas formation via large deformations metric mapping.

作者信息

Lorenzen Peter, Davis Brad, Joshi Sarang

机构信息

Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.

出版信息

Med Image Comput Comput Assist Interv. 2005;8(Pt 2):411-8. doi: 10.1007/11566489_51.

Abstract

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 intra-population 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 Fréchet 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?

摘要

人口图谱的构建是医学图像分析中的一个关键问题,尤其是在脑图谱绘制方面。大量图像被映射到一个公共坐标系中,以研究群体内部的变异性和群体间的差异,提供功能位点的体素级映射,并通过解剖标签的配准来促进组织和物体的分割。我们通过大变形度量映射将无偏图谱构建问题表述为微分同胚空间中的弗雷歇均值估计。提出了一种计算等速速度场的新方法,并使用熵对图谱的稳定性和鲁棒性进行了分析。我们解决了这样一个问题:构建一个稳定的脑图谱需要多少张图像?

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