Deep learning has received extensive research interest in develo** new medical image
processing algorithms, and deep learning based models have been remarkably successful …

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 …

What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

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 …

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-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 …

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 …

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 …

Prostate cancer biopsy benefits from accurate fusion of transrectal ultrasound (TRUS) and
magnetic resonance (MR) images. In the past few years, convolutional neural networks …