Normalized accurate measurement of longitudinal brain change
Normalized accurate measurement of longitudinal brain change
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DOI：
10.1097/00004728-200105000-00022
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发表时间：
2001-05-01
影响因子：
1.3
通讯作者：
Matthews, PM
中科院分区：
文献类型：
--
作者：
Smith, SM;De Stefano, N;Matthews, PM
目的：定量测量大脑大小和形状的变化(例如，评估萎缩)是当前研究的一个重要领域。变更分析的新方法试图提高稳健性、准确性和自动化程度。方法：提出了一种全自动的纵向变化分析方法，该方法自动分割每幅图像中的脑和非脑组织，配准两幅脑图像，同时利用估计的颅骨图像抑制缩放和倾斜，最后通过跟踪表面点到亚像素的精度来估计脑表面运动。结果和结论：所描述的方法被证明是准确的(接近0.2%的脑体积变化误差)，并且具有很高的稳健性(在不同的数据集的数百次分析中没有失败)。
Purpose: Quantitative measurement of change in brain size and shape (e.g., to estimate atrophy) is an important current area of research. New methods of change analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method has been developed that achieves high estimation accuracy.Method: A fully automated method of longitudinal change analysis is presented here, which automatically segments bl ain from nonbrain in each image, registers the two brain images while using estimated skull images to constrain scaling and skew, and finally estimates brain surface motion by tracking surface points to subvoxel accuracy.Results and Conclusion: The method described has been shown to be accurate (approximate to0.2% brain volume change error) and to achieve high robustness (no failures in several hundred analyses over a range of different data sets).