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 …

Background Recent advances in deep learning techniques have led to improved diagnostic
abilities in ophthalmology. A generative adversarial network (GAN), which consists of two …

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 …

Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …

Clinical trials consume the latter half of the 10 to 15 year, 1.5–2.0 billion USD, development
cycle for bringing a single new drug to market. Hence, a failed trial sinks not only the …

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 …

In this paper, we propose a novel method to realize multi-modal image registration and
fusion in a mutually reinforcing framework, termed as RFNet. We handle the registration in a …

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 …

Multi-modal image registration aims to spatially align two images from different modalities to
make their feature points match with each other. Captured by different sensors, the images …

Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …