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 …

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 …

This work investigates the use of robust optimal transport (OT) for shape matching.
Specifically, we show that recent OT solvers improve both optimization-based and deep …

Multi-contrast magnetic resonance (MR) image registration is useful in the clinic to achieve
fast and accurate imaging-based disease diagnosis and treatment planning. Nevertheless …

In this paper, we introduce CorticalFlow, a new geometric deep-learning model that, given a
3-dimensional image, learns to deform a reference template towards a targeted object. To …

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

Over the past decade, deep learning technologies have greatly advanced the field of
medical image registration. The initial developments, such as ResNet-based and U-Net …

Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard for regional
myocardium deformation and cardiac strain estimation. However, this technique has not …

Deformable image registration (DIR), aiming to find spatial correspondence between
images, is one of the most critical problems in the domain of medical image analysis. In this …

We consider the problem of model reduction of parametrized PDEs where the goal is to
approximate any function belonging to the set of solutions at a reduced computational cost …