Background and objectives Over the past two decades, medical imaging has been
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …

Introduction: Artificial intelligence (AI) is the fascinating result of the convergence of various
technologies, algorithms and approaches. Its role in early detection and diagnosis will be a …

Medical image fusion techniques have been widely used in various clinical applications.
Generalized homomorphic filters have Fourier domain features of input image. In multimodal …

Multimodal medical image fusion is one the most important and useful disease diagnostic
techniques. This research paper proposed a novel neuro-fuzzy hybrid multimodal medical …

Image modalities, such as computed tomography (CT), magnetic resonance imaging (MRI),
single‐photon emission computed tomography (SPECT), and so on, reflect various levels of …

Multimodal medical image sensor fusion (MMISF) has a significant role for better
visualization of the diagnostic statistics computed by integrating the vital information taken …

Medical image fusion is a synthesis of visual information present in any number of medical
imaging inputs into a single fused image without any distortion or loss of detail. It enhances …

In clinical applications, single modality images do not provide sufficient diagnostic
information. Therefore, it is necessary to combine the advantages or complementarities of …

Multimodal medical image fusion technique is one of the most significant and useful disease
investigative techniques by deriving the complementary information from different …

Multimodal Medical fusion imaging is a significant aspect of image-guided medical
diagnosis. A new improved non-sub sampled shearlet transform (NSST) based Multimodal …