Brain segmentation is often the first and most critical step in quantitative analysis of the brain
for many clinical applications, including fetal imaging. Different aspects challenge the …

Background Studies for infants are usually hindered by the insufficient image contrast,
especially for neonates. Prior knowledge, in the form of atlas, can provide additional …

We develop a learning framework for building deformable templates, which play a
fundamental role in many image analysis and computational anatomy tasks. Conventional …

Probabilistic atlases are widely used in the neuroscience community as a tool for providing a
standard space for comparison of subjects and as tissue priors used to enhance the intensity …

Sonography has been widely used to assess fetal growth and identify fetal anomalies, 1 and
although fetal neurosonography can analyze brain surface anatomy and maturation, 2 it has …

BACKGROUND AND PURPOSE: MR imaging provides critical information about fetal brain
growth and development. Currently, morphologic analysis primarily relies on manual …

Fetal MRI is clinically performed to evaluate the brain in cases where an abnormality is
detected by prenatal sonography. These most commonly include ventriculomegaly …

The Fuzzy C-Means (FCM) algorithm is a widely used and flexible approach to automated
image segmentation, especially in the field of brain tissue segmentation from 3D MRI, where …

The subthalamic nucleus (STh) is a small subcortical structure which is involved in
regulating motor as well as cognitive functions. Due to its small size and close proximity to …

We describe a framework for creating a time-resolved group average template of the
developing brain using advanced multi-shell high angular resolution diffusion imaging data …