Abstract
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 datasets of segmented fetal brains. Here we introduce a publicly available dataset 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 dataset for the development of automatic algorithms.
Highlights
Background & SummaryCongenital disorders are one of the leading causes of neonatal mortality worldwide
We present a unique dataset (FeTA – Fetal Tissue Annotation and Segmentation Dataset), consisting of SR fetal brain volumes that have been reconstructed from multiple clinically acquired single shot fast spin echo (ssFSE) scans, as well as a manual segmentation of each brain into seven different brain tissues
We manually reviewed the acquired fetal brain images for quality in order to compile a stack of images
Summary
Background & SummaryCongenital disorders are one of the leading causes of neonatal mortality worldwide (http://www.who.int/gho/child_health/mortality/causes/en/). Congenital disorders are one of the leading causes of neonatal mortality worldwide In order to detect and treat congenital disorders, prenatal maternal and fetal healthcare is of the utmost importance. Fetal imaging with ultrasound has been an essential tool in prenatal care for many years. Fetal magnetic resonance imaging (MRI) has started to emerge as an important supplemental tool for providing information about the developing fetus when the ultrasound image is unclear, or for more accurate diagnosis of congenital disorders[1,2,3]. Fetal MRI, especially of the brain, has been shown to be useful in the diagnosis of many congenital disorders such as spina bifida, intrauterine growth retardation, congenital heart disease, lissencephaly, and corpus callosum anomalies[3,4,5,6,7]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
