It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders. To facilitate this analysis, automatic multi-tissue fetal brain segmentation algorithms are needed, which in turn requires open databases of segmented fetal brains. Here we introduce a publicly available database of 50 manually segmented pathological and non-pathological fetal magnetic resonance brain volume reconstructions across a range of gestational ages (20 to 33 weeks) into 7 different tissue categories (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, deep grey matter, brainstem/spinal cord). In addition, we quantitatively evaluate the accuracy of several automatic multi-tissue segmentation algorithms of the developing human fetal brain. Four research groups participated, submitting a total of 10 algorithms, demonstrating the benefits the database for the development of automatic algorithms.
翻译:对发育中的人类胎儿大脑进行定量分析至关重要,以便充分理解正常胎儿和先天性紊乱者的神经发育。为了便于进行这一分析,需要自动的多组织胎儿脑分解算法,这反过来又需要开放的胎儿骨骼数据库。在这里,我们引入了一个可公开查阅的50个手动分解病理和非病理胎儿磁共振反应脑体积数据库,覆盖一系列妊娠年龄(20至33周),分为7个不同的组织类别(外脑脊髓液、灰质、白质、心血管、小脑、深灰质、脑激素/脊髓)。此外,我们还从数量上评估了开发人类胎儿大脑的若干自动多分解算法的准确性。四个研究小组共提交了10个算法,展示了数据库对开发自动算法的好处。