Multi-atlas multi-shape segmentation of fetal brain MRI for volumetric and morphometric analysis of ventriculomegaly.
Multi-atlas multi-shape segmentation of fetal brain MRI for volumetric and morphometric analysis of ventriculomegaly.
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DOI：
10.1016/j.neuroimage.2012.01.128
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发表时间：
2012-04-15
期刊：
影响因子：
5.7
通讯作者：
Warfield, Simon K.
中科院分区：
文献类型：
--
作者：
Gholipour, Ali;Akhondi-Asl, Alireza;Estroff, Judy A.;Warfield, Simon K.
运动鲁棒超分辨率胎儿脑MRI的最新发展为体积和形态测量分析提供了巨大的新进展。基于发育中胎儿大脑的体积和形态学生物标志物的体积分析必须包括分割。然而，由于发育中大脑的大小和形状高度可变;可能的结构异常;以及胎儿MRI扫描的分辨率相对较差，因此胎儿大脑MRI的自动分割具有挑战性。为了克服这些局限性，我们提出了一种新的，受约束的，多图集，多形状的自动分割方法，专门解决了分割多个结构具有相似的强度值在具有较强的解剖变异性的主题的挑战。因此，我们已经应用这种方法的形状分割正常，扩张，或融合侧脑室的定量分析脑室扩大（VM），这是一个关键的发现，在胎儿大脑发育的最早阶段，并值得进一步调查。利用这些创新技术，我们引入了新的VM体积和形态生物标志物，将这些值与VM分析的标准方法产生的值进行比较，即，通过在2D超声或2D MRI的手动选择部分上测量心室心房直径（AD）。为此，我们研究了25例正常和异常胎龄（GA）范围为19至39周（平均值=28.26，标准差=6.56）。该异质数据集基本上用于1）验证我们针对正常和异常心室的分割方法;以及2）显示与AD测量相比，所提出的生物标志物可以提供改善的VM检测。
The recent development of motion robust super-resolution fetal brain MRI holds out the potential for dramatic new advances in volumetric and morphometric analysis. Volumetric analysis based on volumetric and morphometric biomarkers of the developing fetal brain must include segmentation. Automatic segmentation of fetal brain MRI is challenging, however, due to the highly variable size and shape of the developing brain; possible structural abnormalities; and the relatively poor resolution of fetal MRI scans. To overcome these limitations, we present a novel, constrained, multi-atlas, multi-shape automatic segmentation method that specifically addresses the challenge of segmenting multiple structures with similar intensity values in subjects with strong anatomic variability. Accordingly, we have applied this method to shape segmentation of normal, dilated, or fused lateral ventricles for quantitative analysis of ventriculomegaly (VM), which is a pivotal finding in the earliest stages of fetal brain development, and warrants further investigation. Utilizing these innovative techniques, we introduce novel volumetric and morphometric biomarkers of VM comparing these values to those that are generated by standard methods of VM analysis, i.e., by measuring the ventricular atrial diameter (AD) on manually selected sections of 2D ultrasound or 2D MRI. To this end, we studied 25 normal and abnormal fetuses in the gestation age (GA) range of 19 to 39 weeks (mean=28.26, stdev=6.56). This heterogenous dataset was essentially used to 1) validate our segmentation method for normal and abnormal ventricles; and 2) show that the proposed biomarkers may provide improved detection of VM as compared to the AD measurement.
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影响因子：
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