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 …

Image registration is a fundamental task in multiple medical image analysis applications.
With the advent of deep learning, there have been significant advances in algorithmic …

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

Medical images are a rich source of invaluable necessary information used by clinicians.
Recent technologies have introduced many advancements for exploiting the most of this …

Medical image registration is a vital component of many medical procedures, such as image-
guided radiotherapy (IGRT), as it allows for more accurate dose-delivery and better …

In this paper, we introduce PCR-CG: a novel 3D point cloud registration module explicitly
embedding the color signals into geometry representation. Different from the previous SOTA …

Purpose The accuracy of minimally invasive, intracranial neurosurgery can be challenged
by deformation of brain tissue–eg, up to 10 mm due to egress of cerebrospinal fluid during …

Image registration is a critical component in the applications of various medical image
analyses. In recent years, there has been a tremendous surge in the development of deep …

Conventional medical image registration approaches directly optimize over the parameters
of a transformation model. These approaches have been highly successful and are used …

Deformable templates are essential to large-scale medical image registration, segmentation,
and population analysis. Current conventional and deep network-based methods for …