Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest
Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest
复制标题
DOI：
10.1016/j.neuroimage.2007.11.034
复制
发表时间：
2008-04-01
期刊：
影响因子：
5.7
通讯作者：
Hammers, Alexander
中科院分区：
文献类型：
--
作者：
Gousias, Ioannis S.;Rueckert, Daniel;Hammers, Alexander
不同年龄段大脑的三维图谱和数据库有助于神经解剖学的描述和大脑生长发育的监测。由于与成人相比的结构差异，幼儿的大脑分割具有挑战性。我们开发了一种基于既定算法的方法，用于将幼儿的大脑自动分割成 83 个感兴趣区域 (ROI)，并将其应用于 33 名早产的 2 岁受试者的样本组。该算法使用来自 30 张正常成人大脑磁共振 (MR) 图像的先验信息，这些图像已被手动分割以创建 30 个图集，每个图集标记 83 个解剖结构。使用基于自由变形的非刚性配准将这些成人图谱中的每一个都配准到每张 2 岁的目标 MR 图像。每个成人图谱的标签传播将每个 2 岁儿童的大脑分割为 83 个 ROI。最终的分割是通过使用决策融合组合 30 个传播的成人图集来获得的，从而提高了个体传播的准确性。我们通过使用相似性指数（SI）（空间重叠的度量（平均交集））将自动方法与三个代表性的手动分割体积区域（皮质下尾状核、新皮质中央前回旋和古皮质海马）进行比较来验证该算法。这三种结构的自动分割与手动分割的 SI 结果分别为 0.90 +/- 0.01、0.90 +/- 0.01 和 0.88 +/- 0.03。这种配准方法可以快速构建 2 岁儿童的自动标记的特定年龄的大脑图谱。 (c) 2007 Elsevier Inc. 保留所有权利。
Three-dimensional atlases and databases of the brain at different ages facilitate the description of neuroanatomy and the monitoring of cerebral growth and development. Brain segmentation is challenging in young children due to structural differences compared to adults. We have developed a method, based on established algorithms, for automatic segmentation of young children's brains into 83 regions of interest (ROIs), and applied this to an exemplar group of 33 2-year-old subjects who had been born prematurely. The algorithm uses prior information from 30 normal adult brain magnetic resonance (MR) images, which had been manually segmented to create 30 atlases, each labeling 83 anatomical structures. Each of these adult atlases was registered to each 2-year-old target MR image using non-rigid registration based on free-form deformations. Label propagation from each adult atlas yielded a segmentation of each 2-year-old brain into 83 ROIs. The final segmentation was obtained by combination of the 30 propagated adult atlases using decision fusion, improving accuracy over individual propagations. We validated this algorithm by comparing the automatic approach with three representative manually segmented volumetric regions (the subcortical caudate nucleus, the neocortical precentral gyros and the archicortical hippocampus) using similarity indices (SI), a measure of spatial overlap (intersection over average). SI results for automatic versus manual segmentations for these three structures were 0.90 +/- 0.01, 0.90 +/- 0.01 and 0.88 +/- 0.03 respectively. This registration approach allows the rapid construction of automatically labelled age-specific brain atlases for children at the age of 2 years. (c) 2007 Elsevier Inc. All rights reserved.