Multimodal image fusion plays an essential role in medical image analysis and application,
where computed tomography (CT), magnetic resonance (MR), single-photon emission …

Multi-modal medical image fusion aims to integrate distinct imaging modalities to yield more
comprehensive and precise medical images, which can benefit the subsequent image …

Medical imaging plays a pivotal role in the clinical diagnosis of brain disease. There are
many imaging methods to detect the state of tissues in the brain. While these imaging …

Multimodal medical image fusion aims to merge saliency and complementary information
from different source images to assist in biomedical diagnoses. How to effectively utilize …

Recently, the rapid development of the Internet of Things has contributed to the generation
of telemedicine. However, online diagnoses by doctors require the analyses of multiple multi …

Multi-modal medical image fusion (MMIF) is used to merge multiple modes of medical
images for better imaging quality and more comprehensive information, such that enhancing …

Background In medical diagnosis of brain, the role of multi-modal medical image fusion is
becoming more prominent. Among them, there is no lack of filtering layered fusion and …

Most multimodal medical image fusion (MMIF) methods suffer from insufficient
complementary feature extraction and luminance degradation, such that the fused results …

Multimodal medical image fusion fuses images with different modalities and provides more
comprehensive and integrated diagnostic information. However, current multimodal image …

It is crucial to integrate the complementary information of multimodal medical images for
enhancing the image quality in clinical diagnosis. Convolutional neural network (CNN) …