Automated extraction of nested sulcus features from human brain MRI data.
Automated extraction of nested sulcus features from human brain MRI data.
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从人脑 MRI 数据中自动提取嵌套沟特征。
DOI：
10.1109/embc.2012.6346949
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Klein,Arno
中科院分区：
文献类型：
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作者：
Bao,ForrestSheng;Giard,Joachim;Tourville,Jason;Klein,Arno
从人脑磁共振成像数据中提取与大脑皮层中的褶皱相关的对象（“沟特征”）在形态测量、基于地标的配准和解剖标记中具有应用。在以前的工作中，沟特征，如表面，fundi和坑已被单独提取。在这里，我们定义和提取嵌套沟功能的分层方式从皮质表面网格曲率或深度值。我们的实验结果表明，嵌套的功能是使用其他方法分别提取的功能相媲美，他们是一致的主题和手动标签的边界。我们的开源特征提取软件将作为Mindboggle项目的一部分免费提供（www.mindboggle.info）。
Extracting objects related to a fold in the cerebral cortex (“sulcus features”) from human brain magnetic resonance imaging data has applications in morphometry, landmark-based registration, and anatomical labeling. In prior work, sulcus features such as surfaces, fundi and pits have been extracted separately. Here we define and extract nested sulcus features in a hierarchical manner from a cortical surface mesh having curvature or depth values. Our experimental results show that the nested features are comparable to features extracted separately using other methods, and that they are consistent across subjects and with manual label boundaries. Our open source feature extraction software will be made freely available as part of the Mindboggle project (http://www.mindboggle.info).