Mindboggle: automated brain labeling with multiple atlases.
Mindboggle: automated brain labeling with multiple atlases.
复制标题
MindBoggle：具有多个地图集的自动脑标记。
DOI：
10.1186/1471-2342-5-7
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发表时间：
2005-10-05
影响因子：
2.7
通讯作者：
Hirsch, Joy
中科院分区：
文献类型：
--
作者：
Klein, Arno;Mensh, Brett;Ghosh, Satrajit;Tourville, Jason;Hirsch, Joy
要对多个人的大脑结构或活动做出推断，首先需要确定他们图像数据的结构对应关系。我们最近开发了一种全自动的、功能匹配的方法，可以将解剖标签分配给人脑MRI数据中的皮质结构和活动。标签分配基于已标记图谱和未标记图像数据之间的结构对应，其中图谱由手动分配给单个脑图像的一组标签组成。在本工作中，我们研究了使用不同数量的单个地图集对人脑图像数据进行非线性标注的影响。20个人类受试者中每个人的每个脑图像体素都被其余19个图集中的每一个使用Mindbogle分配了一个标签。最常见的标签被选择，并基于分配该标签的地图集的数量被给予置信度评级。将为每个受试者大脑自动分配的标签与该受试者(其图谱)的手动标签进行比较。与最近将主题数据转换到标记的、概率的地图集空间(从地图集数据库构建)的方法不同，Mindbogler通过数据库中的每个地图集独立地标记主题。当Mindbogble用至少四个图谱标记受试者的大脑图像时，结果与共同注册的手动标签的标记一致性显著高于只使用单一图谱的情况。不同数量的地图集为各个大脑区域提供了显著更高的标记协议。增加用于自动标记人类受试者大脑的参照脑的数量提高了相对于手动分配的标记的标记准确性。Mindbogger软件可以根据标签的概率分配为标签提供置信度度量，并可应用于大型脑图像数据库。
To make inferences about brain structures or activity across multiple individuals, one first needs to determine the structural correspondences across their image data. We have recently developed Mindboggle as a fully automated, feature-matching approach to assign anatomical labels to cortical structures and activity in human brain MRI data. Label assignment is based on structural correspondences between labeled atlases and unlabeled image data, where an atlas consists of a set of labels manually assigned to a single brain image. In the present work, we study the influence of using variable numbers of individual atlases to nonlinearly label human brain image data. Each brain image voxel of each of 20 human subjects is assigned a label by each of the remaining 19 atlases using Mindboggle. The most common label is selected and is given a confidence rating based on the number of atlases that assigned that label. The automatically assigned labels for each subject brain are compared with the manual labels for that subject (its atlas). Unlike recent approaches that transform subject data to a labeled, probabilistic atlas space (constructed from a database of atlases), Mindboggle labels a subject by each atlas in a database independently. When Mindboggle labels a human subject's brain image with at least four atlases, the resulting label agreement with coregistered manual labels is significantly higher than when only a single atlas is used. Different numbers of atlases provide significantly higher label agreements for individual brain regions. Increasing the number of reference brains used to automatically label a human subject brain improves labeling accuracy with respect to manually assigned labels. Mindboggle software can provide confidence measures for labels based on probabilistic assignment of labels and could be applied to large databases of brain images.