Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

This paper presents a review of deep learning (DL)-based medical image registration
methods. We summarized the latest developments and applications of DL-based registration …

Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

The establishment of image correspondence through robust image registration is critical to
many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitoring …

Generative adversarial networks (GANs) and their extensions have carved open many
exciting ways to tackle well known and challenging medical image analysis problems such …

Image registration is a fundamental task in medical image analysis. Recently, many deep
learning based image registration methods have been extensively investigated due to their …

We propose to learn a low-dimensional probabilistic deformation model from data which can
be used for the registration and the analysis of deformations. The latent variable model …

Deep convolutional networks have demonstrated state-of-the-art performance on various
challenging medical image processing tasks. Leveraging images from different modalities …

Deep neural networks represent, nowadays, the most effective machine learning technology
in biomedical domain. In this domain, the different areas of interest concern the Omics (study …

Image-guided interventions are saving the lives of a large number of patients where the
image registration should indeed be considered as the most complex and complicated issue …