Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

What are the brain structural correlates of interindividual differences in behaviour? More
than a decade ago, advances in structural MRI opened promising new avenues to address …

Imaging technologies are increasingly used to generate high-resolution reference maps of
brain structure and function. Comparing experimentally generated maps to these reference …

We propose and empirically support a parsimonious account of intrinsic, brain-wide
spatiotemporal organization arising from traveling waves linked to arousal. We hypothesize …

We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical
image registration. Traditional registration methods optimize an objective function for each …

Despite advances in data augmentation and transfer learning, convolutional neural
networks (CNNs) difficultly generalise to unseen domains. When segmenting brain scans …

Image segmentation is an important task in many medical applications. Methods based on
convolutional neural networks attain state-of-the-art accuracy; however, they typically rely on …

Classical deformable registration techniques achieve impressive results and offer a rigorous
theoretical treatment, but are computationally intensive since they solve an optimization …

A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete
neurobiological “atoms”. Resting-state functional magnetic resonance imaging (rs-fMRI) …

We present a fast learning-based algorithm for deformable, pairwise 3D medical image
registration. Current registration methods optimize an objective function independently for …