Spatio-Temporal Regularization for Longitudinal Registration to Subject-Specific 3d Template.
Spatio-Temporal Regularization for Longitudinal Registration to Subject-Specific 3d Template.
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DOI：
10.1371/journal.pone.0133352
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Collins DL
中科院分区：
文献类型：
--
作者：
Guizard N;Fonov VS;García-Lorenzo D;Nakamura K;Aubert-Broche B;Collins DL
神经退行性疾病，如阿尔茨海默氏病，在临床症状出现之前，会出现微妙的脑解剖学变化。手动结构分割是漫长而繁琐的，尽管存在自动方法，但它们通常以横截面的方式进行，其中每个时间点独立分析。采用这种分析方法，可能会引入偏差、误差和纵向噪声。由于MR扫描仪和其他生理效应引起的噪声也可能在测量中引入可变性。我们建议使用4D非线性配准与时空正则化，以纠正潜在的纵向不一致的背景下，结构分割。这篇文章的主要贡献是使用个人模板创建与时空正则化的变形领域为每个主题。我们用不同的真实的MRI数据集验证了我们的方法，将其与FreeSurfer，SPM 12，QUARC，TBM和KNBSI等可用的纵向方法进行比较，并证明空间局部时间正则化产生更一致的全局结构变化率，从而具有更好的统计能力来检测随时间推移和人群之间的显著变化。
Neurodegenerative diseases such as Alzheimer's disease present subtle anatomical brain changes before the appearance of clinical symptoms. Manual structure segmentation is long and tedious and although automatic methods exist, they are often performed in a cross-sectional manner where each time-point is analyzed independently. With such analysis methods, bias, error and longitudinal noise may be introduced. Noise due to MR scanners and other physiological effects may also introduce variability in the measurement. We propose to use 4D non-linear registration with spatio-temporal regularization to correct for potential longitudinal inconsistencies in the context of structure segmentation. The major contribution of this article is the use of individual template creation with spatio-temporal regularization of the deformation fields for each subject. We validate our method with different sets of real MRI data, compare it to available longitudinal methods such as FreeSurfer, SPM12, QUARC, TBM, and KNBSI, and demonstrate that spatially local temporal regularization yields more consistent rates of change of global structures resulting in better statistical power to detect significant changes over time and between populations.
DOI：
10.1117/12.844526
发表时间：
2010-03-12
期刊：
Proceedings of SPIE--the International Society for Optical Engineering
影响因子：
--
作者：
Sadeghi N;Prastawa M;Gilmore JH;Lin W;Gerig G
通讯作者：
Gerig G