Images captured from a single or multiple imaging sensors with considerable focus or
numerous exposures of the same or different modalities do not provide all relevant …

Today, medical images play a crucial role in obtaining relevant medical information for
clinical purposes. However, the quality of medical images must be analyzed and improved …

Medical image fusion has brought practical applications in clinical diagnosis. However,
image fusion methods still face challenges because of problems with the quality of the input …

Since vectors include direction and magnitude, they have more information than scalars. So,
converting the scalar images into the vector field leads achieving much information about …

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

Many medical image fusion algorithms have been developed with the aim at enriching
visual information for clinical diagnosis. However, these algorithms always suffer from …

To solve problems of brightness and detail information loss in infrared and visible image
fusion, an effective infrared and visible image fusion method using rolling guidance filtering …

Considering that coupled dictionary learning (CDL) method can obtain a reasonable linear
mathematical relationship between resource images, we propose a novel CDL-based …

The synthesis of visual information from multiple medical imaging inputs to a single fused
image without any loss of detail and distortion is known as multimodal medical image fusion …

Fusion plays a pivotal role in the field of clinical processing; it could minimize the impacts of
human errors, enhance diagnostic performance, and save manpower and time. Thus, the …