In recent years, deep convolutional neural networks (CNNs) have shown record-shattering
performance in a variety of computer vision problems, such as visual object recognition …

Abstract The Developing Human Connectome Project (dHCP) seeks to create the first 4-
dimensional connectome of early life. Understanding this connectome in detail may provide …

We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic
segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is …

In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical
sensitivity and spatial localisation of group studies, and cortical surface-based alignment …

Functional MRI (fMRI) studies have traditionally relied on intersubject normalization based
on global brain morphology, which cannot establish proper functional correspondence …

We propose a method for constructing a spatio-temporal cortical surface atlas of neonatal
brains aged between 36 and 44 weeks of post-menstrual age (PMA) at the time of scan. The …

This paper presents a new framework for capturing large and complex deformations in
image registration and atlas construction. This challenging and recurrent problem in …

Studies in comparative neuroanatomy and of the fossil record demonstrate the influence of
socio-ecological niches on the morphology of the cerebral cortex, but have led to oftentimes …

The alignment of brain imaging data for functional neuroimaging studies is challenging due
to the discrepancy between correspondence of morphology, and equivalence of functional …

Cortical surface registration is an essential step and prerequisite for surface-based
neuroimaging analysis. It aligns cortical surfaces across individuals and time points to …