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

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 …

Deep learning-based methods have recently demonstrated promising results in deformable
image registration for a wide range of medical image analysis tasks. However, existing deep …

Deformable image registration is a fundamental step for medical image analysis. Recently
transformers have been used for registration and outperformed Convolutional Neural …

Due to their extreme long-range modeling capability, vision transformer-based networks
have become increasingly popular in deformable image registration. We believe, however …

3D medical image registration is of great clinical importance. However, supervised learning
methods require a large amount of accurately annotated corresponding control points (or …

This paper introduces a novel top-down representation approach for deformable image
registration which estimates the deformation field by capturing various short-and long-range …

Complicated deformation problems are frequently encountered in medical image
registration tasks. Although various advanced registration models have been proposed …

We propose a Dual-stream Pyramid Registration Network (referred as Dual-PRNet) for
unsupervised 3D brain image registration. Unlike recent CNN-based registration …

As with any data fusion task, the front-end of the pipeline for image fusion, aiming to collect
multitudinous physical properties from multimodal images taken by different types of …