Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …

This paper presents a review of automated image registration methodologies that have been
used in the medical field. The aim of this paper is to be an introduction to the field, provide …

Every year, millions of brain magnetic resonance imaging (MRI) scans are acquired in
hospitals across the world. These have the potential to revolutionize our understanding of …

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …

This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver
registration for image-pairs works by patch-wise prediction of a deformation model based …

Longitudinal image analysis has become increasingly important in clinical studies of normal
aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the …

The United States National Institutes of Health (NIH) commit significant support to open-
source data and software resources in order to foment reproducibility in the biomedical …

Spatial normalization, registration, and segmentation techniques for Magnetic Resonance
Imaging (MRI) often use a target or template volume to facilitate processing, take advantage …