Atlas-based segmentation of developing tissues in the human brain with quantitative validation in young fetuses.
Atlas-based segmentation of developing tissues in the human brain with quantitative validation in young fetuses.
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DOI：
10.1002/hbm.20935
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发表时间：
2010-09
影响因子：
4.8
通讯作者：
Studholme, Colin
中科院分区：
文献类型：
--
作者：
Habas, Piotr A.;Kim, Kio;Rousseau, Francois;Glenn, Orit A.;Barkovich, A. James;Studholme, Colin
使用磁共振（MR）对人类胎儿进行成像是定量研究子宫内正常和异常脑发育的重要工具。然而，由于胎儿和成人大脑之间的组织类型、组织性质和组织分布的根本差异，为成人大脑解剖学开发的自动组织分割技术不适合于该数据。在本文中，我们描述的方法，自动地图集为基础的分割个别组织类型的运动校正的三维体积重建从临床MR扫描胎儿大脑。为了生成解剖学上正确的自动分割，我们创建了一组准确的手动描绘，并建立了子宫内组织分布的3D统计图谱，其中包括发育中的灰色和白色物质以及瞬态组织类型，如生发基质。概率图谱与无偏平均形状和强度模板相关联，用于将新的受试者图像配准到图谱的空间。在一组14个胎儿MR扫描（胎龄20.57-22.86周）上进行的组织标记的定量全脑3D验证表明，这种基于图谱的EM分割方法对于胎儿脑中的主要组织类型实现了一致的高DSC性能。这项工作表明，大脑发育的可靠措施，可以自动从临床MR成像，开辟了进一步的三维体积和形态学研究与多个胎儿科目的可能性。
Imaging of the human fetus using magnetic resonance (MR) is an essential tool for quantitative studies of normal as well as abnormal brain development in utero. However, because of fundamental differences in tissue types, tissue properties and tissue distribution between the fetal and adult brain, automated tissue segmentation techniques developed for adult brain anatomy are unsuitable for this data. In this paper, we describe methodology for automatic atlas-based segmentation of individual tissue types in motion-corrected 3D volumes reconstructed from clinical MR scans of the fetal brain. To generate anatomically correct automatic segmentations, we create a set of accurate manual delineations and build an in utero 3D statistical atlas of tissue distribution incorporating developing grey and white matter as well as transient tissue types such as the germinal matrix. The probabilistic atlas is associated with an unbiased average shape and intensity template for registration of new subject images to the space of the atlas. Quantitative whole brain 3D validation of tissue labeling performed on a set of 14 fetal MR scans (20.57–22.86 weeks gestational age) demonstrates that this atlas-based EM segmentation approach achieves consistently high DSC performance for the main tissue types in the fetal brain. This work indicates that reliable measures of brain development can be automatically derived from clinical MR imaging and opens up possibility of further 3D volumetric and morphometric studies with multiple fetal subjects.
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