A novel framework for longitudinal atlas construction with groupwise registration of subject image sequences.
A novel framework for longitudinal atlas construction with groupwise registration of subject image sequences.
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DOI：
10.1016/j.neuroimage.2011.07.095
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发表时间：
2012-01-16
期刊：
影响因子：
5.7
通讯作者：
Shen, Dinggang
中科院分区：
文献类型：
--
作者：
Liao, Shu;Jia, Hongjun;Wu, Guorong;Shen, Dinggang
纵向图谱的构建在医学图像分析中起着重要的作用。给定一组来自不同学科的纵向图像，纵向图谱构建的任务是构建一个能够代表种群解剖变化趋势的图谱序列。纵向地图集的构建面临的主要挑战是如何有效地结合特定学科信息和人口信息来构建无偏地图集。针对这一挑战，本文提出了一种新的分组纵向图谱构建框架，该框架的主要贡献在于：(1)通过构建每个学科的生长模型来获取特定学科的纵向信息。(2)通过对所有主体图像序列进行分组配准构建纵向地图集序列，将每个主体图像序列转换为地图集空间仅需一次变换。构造的纵向地图集是无偏的，没有明确的模板假设。(3)所提出的方法是通用的，每个主体的纵向图像的数量和拍摄的时间点可以不同。该方法在两个纵向数据库（BLSA和ADNI数据库）上进行了广泛的评估，以构建纵向图谱序列。并与基于核回归的时域纵向图谱构建算法进行了比较。实验结果表明，与对比方法相比，该方法在两个数据库上均能获得更高的配准精度和更一致的时空对应关系。
Longitudinal atlas construction plays an important role in medical image analysis. Given a set of longitudinal images from different subjects, the task of longitudinal atlas construction is to build an atlas sequence which can represent the trend of anatomical changes of the population. The major challenge for longitudinal atlas construction is how to effectively incorporate both the subject-specific information and population information to build the unbiased atlases. In this paper, a novel groupwise longitudinal atlas construction framework is proposed to address this challenge, and the main contributions of the proposed framework lie in the following aspects: (1) The subject-specific longitudinal information is captured by building the growth model for each subject. (2) The longitudinal atlas sequence is constructed by performing groupwise registration among all the subject image sequences, and only one transformation is needed to transform each subject’s image sequence to the atlas space. The constructed longitudinal atlases are unbiased and no explicit template is assumed. (3) The proposed method is general, where the number of longitudinal images of each subject and the time points at which they are taken can be different. The proposed method is extensively evaluated on two longitudinal databases, namely the BLSA and ADNI databases, to construct the longitudinal atlas sequence. It is also compared with a state-of-the-art longitudinal atlas construction algorithm based on kernel regression on the temporal domain. Experimental results demonstrate that the proposed method consistently achieves higher registration accuracies and more consistent spatial-temporal correspondences than the compared method on both databases.
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DOI：
10.1023/b:visi.0000043755.93987.aa
发表时间：
2005-02-01
影响因子：
19.5
作者：
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