A spatio-temporal latent atlas for semi-supervised learning of fetal brain segmentations and morphological age estimation
A spatio-temporal latent atlas for semi-supervised learning of fetal brain segmentations and morphological age estimation
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DOI：
10.1016/j.media.2013.08.004
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发表时间：
2014-01-01
影响因子：
10.9
通讯作者：
Langs, Georg
中科院分区：
文献类型：
--
作者：
Dittrich, Eva;Raviv, Tammy Riklin;Langs, Georg
产前神经成像需要反映胎儿大脑发育正常谱的参考模型，并总结来自个体代表性样本的观察结果。收集足够大的手动注释数据的数据集来构建快速发展结构的全面体内图谱是具有挑战性的，但对于大群体研究和临床应用是必要的。我们提出了一种半监督学习的胎儿大脑发育的时空潜在的图集，以及相应的分割新兴的大脑结构，如脑室或皮质的方法。该图谱是基于少数实例的注释，而大量的成像数据没有注释。它模拟了整个种群的形态和发育变异性。此外，它作为基础的结构的形态年龄的估计，其偏离标称胎龄在病理评估。实验结果表明，覆盖妊娠期20-30周的分割精度达到最低限度的注释，和形态学年龄估计的精度。对患有无脑回畸形的胎儿的年龄估计结果表明，与对照组相比，他们检测到年龄偏移的显著差异。(C)2013年由Elsevier B. V.出版
Prenatal neuroimaging requires reference models that reflect the normal spectrum of fetal brain development, and summarize observations from a representative sample of individuals. Collecting a sufficiently large data set of manually annotated data to construct a comprehensive in vivo atlas of rapidly developing structures is challenging but necessary for large population studies and clinical application. We propose a method for the semi-supervised learning of a spatio-temporal latent atlas of fetal brain development, and corresponding segmentations of emerging cerebral structures, such as the ventricles or cortex. The atlas is based on the annotation of a few examples, and a large number of imaging data without annotation. It models the morphological and developmental variability across the population. Furthermore, it serves as basis for the estimation of a structures' morphological age, and its deviation from the nominal gestational age during the assessment of pathologies. Experimental results covering the gestational period of 20-30 gestational weeks demonstrate segmentation accuracy achievable with minimal annotation, and precision of morphological age estimation. Age estimation results on fetuses suffering from lissencephaly demonstrate that they detect significant differences in the age offset compared to a control group. (C) 2013 Published by Elsevier B.V.