Physical Science and Technology College, Zhengzhou University, Zhengzhou, China.
J Magn Reson Imaging. 2010 Oct;32(4):830-5. doi: 10.1002/jmri.22283.
To automatically extract regions of interest (ROIs) and simultaneously preserve the anatomical characteristics of each individual, we developed a new atlas-based method utilizing a pair of coregistered brain template and digital atlas.
Unlike the previous atlas-based method, this method treats each individual as the target image, and the template and atlas are each transformed to register with the individual. To evaluate the accuracy of this method we implemented it in extracting the hippocampus from two groups of T(2)-weighted structural images with different spatial resolutions and a group of T(2)*-weighted functional images. Furthermore, the results were compared against a manually segmented hippocampus and an atlas-derived hippocampus.
Jaccard similarity (JS) reached 84.7%-90.5%, and relative error in volume (RV) was 4.8%-12.7%. The consistency observed between the results of the proposed method and manual drawing was therefore considerable.
We developed a new atlas-based method for ROI extraction that can automatically extract ROI and simultaneously preserve each individual's unique anatomical characteristics.
为了自动提取感兴趣区域(ROI),同时保留每个个体的解剖特征,我们开发了一种新的基于图谱的方法,利用一对配准的大脑模板和数字图谱。
与以前的基于图谱的方法不同,该方法将每个个体视为目标图像,而模板和图谱都被转换为与个体配准。为了评估该方法的准确性,我们将其应用于从两组具有不同空间分辨率的 T(2)加权结构图像和一组 T(2)*-加权功能图像中提取海马体。此外,还将结果与手动分割的海马体和图谱衍生的海马体进行了比较。
Jaccard 相似性(JS)达到 84.7%-90.5%,体积相对误差(RV)为 4.8%-12.7%。因此,所提出的方法和手动绘图的结果之间的一致性是相当可观的。
我们开发了一种新的基于图谱的 ROI 提取方法,该方法可以自动提取 ROI,并同时保留每个个体独特的解剖特征。