The image fusion methods based on deep learning has become a research hotspot in the
field of computer vision in recent years. This paper reviews these methods from five aspects …

Medical image fusion techniques can fuse medical images from different morphologies to
make the medical diagnosis more reliable and accurate, which play an increasingly …

The medical image fusion is the process of coalescing multiple images from multiple
imaging modalities to obtain a fused image with a large amount of information for increasing …

In recent times, several medical image fusion techniques based on the convolutional neural
network (CNN) have been proposed for various medical imaging fusion tasks. However …

This paper proposed a novel fusion scheme for muti-modal medical images that utilizes both
the features of the multi-scale transformation and deep convolutional neural network. Firstly …

Medical image fusion technique can help the physician to execute combined diagnosis,
preoperative planning, intraoperative guidance, and interventional treatment in many clinical …

Medical image fusion technology synthesizes complementary information from multimodal
medical images. This technology is playing an increasingly important role in clinical …

Medical image fusion techniques can further improve the accuracy and time efficiency of
clinical diagnosis by obtaining comprehensive salient features and detail information from …

Medical image fusion aims to derive complementary information from medical images with
different modalities and is becoming increasingly important in clinical applications. The …

Multi-modal medical image fusion (MMIF) has found wide application in the field of disease
diagnosis and surgical guidance. Despite the popularity of deep learning (DL)-based fusion …