The usage of artificial intelligence (AI) based applications has gained popularity in the
medical tourism industry. By giving patients personalized recommendations based on their …

Multi-modal medical image fusion (MMIF) is a valuable approach to integrating functional
metabolic information and tissue structural details from different modalities, which facilitates …

Multimodal medical image is an effective method to solve a series of clinical problems, such
as clinical diagnosis and postoperative treatment. In this study, a medical image fusion …

Imaging data fusion is becoming a bottleneck in clinical applications and translational
research in medical imaging. This study aims to incorporate a novel multimodality medical …

Medical image fusion can provide a synthetical presentation of human tissue by fusing the
complementary features of different source images, such as computerized tomography (CT) …

The synthesis of medical images plays a pivotal role in image-based disease diagnosis. In
recent years, numerous medical image synthesis methods have been proposed …

Existing multi-modal image fusion methods utilize multi-modal images as input that require
multiple imaging of patients causing harm to patients' bodies and large costs, moreover …

A composite image of infrared and visible images should contain salient features of two
source images which come from different sensors in the same scene. In this paper, we …

Medical image fusion is of great significance in medical analysis and disease diagnosis.
Until now, there are still limitations to the current fusion methods to our current knowledge …

An algorithm for a sharpness evaluation of microscopic images based on non-subsampled
shearlet wave transform (NSST) and variance is proposed in the present study for the …