Image fusion meets deep learning: A survey and perspective
Image fusion, which refers to extracting and then combining the most meaningful information
from different source images, aims to generate a single image that is more informative and …
from different source images, aims to generate a single image that is more informative and …
A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics
Background and objectives Over the past two decades, medical imaging has been
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
Cddfuse: Correlation-driven dual-branch feature decomposition for multi-modality image fusion
Multi-modality (MM) image fusion aims to render fused images that maintain the merits of
different modalities, eg, functional highlight and detailed textures. To tackle the challenge in …
different modalities, eg, functional highlight and detailed textures. To tackle the challenge in …
DDFM: denoising diffusion model for multi-modality image fusion
Multi-modality image fusion aims to combine different modalities to produce fused images
that retain the complementary features of each modality, such as functional highlights and …
that retain the complementary features of each modality, such as functional highlights and …
Current advances and future perspectives of image fusion: A comprehensive review
Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …
world than a single modality alone. Infrared images discriminate targets with respect to their …
Image fusion techniques: a survey
The necessity of image fusion is growing in recently in image processing applications due to
the tremendous amount of acquisition systems. Fusion of images is defined as an alignment …
the tremendous amount of acquisition systems. Fusion of images is defined as an alignment …
Multimodal medical image fusion review: Theoretical background and recent advances
Multimodal medical image fusion consists in combining two or more images of the same or
different modalities aiming to improve the image content, and preserve information. The …
different modalities aiming to improve the image content, and preserve information. The …
Deep learning-based multi-focus image fusion: A survey and a comparative study
X Zhang - IEEE Transactions on Pattern Analysis and Machine …, 2021 - ieeexplore.ieee.org
Multi-focus image fusion (MFIF) is an important area in image processing. Since 2017, deep
learning has been introduced to the field of MFIF and various methods have been proposed …
learning has been introduced to the field of MFIF and various methods have been proposed …
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Information …, 2023 - Elsevier
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
An overview on spectral and spatial information fusion for hyperspectral image classification: Current trends and challenges
M Imani, H Ghassemian - Information fusion, 2020 - Elsevier
Hyperspectral images (HSIs) have a cube form containing spatial information in two
dimensions and rich spectral information in the third one. The high volume of spectral bands …
dimensions and rich spectral information in the third one. The high volume of spectral bands …