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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 …
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 …
A comparative review on multi-modal sensors fusion based on deep learning
The wide deployment of multi-modal sensors in various areas generates vast amounts of
data with characteristics of high volume, wide variety, and high integrity. However, traditional …
data with characteristics of high volume, wide variety, and high integrity. However, traditional …
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 …
A review of multimodal medical image fusion techniques
B Huang, F Yang, M Yin, X Mo… - … mathematical methods in …, 2020 - Wiley Online Library
The medical image fusion is the process of coalescing multiple images from multiple
imaging modalities to obtain a fused image with a large amount of information for increasing …
imaging modalities to obtain a fused image with a large amount of information for increasing …
Gesenet: A general semantic-guided network with couple mask ensemble for medical image fusion
At present, multimodal medical image fusion technology has become an essential means for
researchers and doctors to predict diseases and study pathology. Nevertheless, how to …
researchers and doctors to predict diseases and study pathology. Nevertheless, how to …
Medical image fusion based on convolutional neural networks and non-subsampled contourlet transform
Although many powerful convolutional neural networks (CNN) have been applied to various
image processing fields, due to the lack of datasets for network training and the significant …
image processing fields, due to the lack of datasets for network training and the significant …
Multimodal medical image sensor fusion framework using cascade of wavelet and contourlet transform domains
Multimodal medical image fusion is effectuated to minimize the redundancy while
augmenting the necessary information from the input images acquired using different …
augmenting the necessary information from the input images acquired using different …
A fusion algorithm for infrared and visible images based on adaptive dual-channel unit-linking PCNN in NSCT domain
In this paper, a novel fusion algorithm based on the adaptive dual-channel unit-linking pulse
coupled neural network (PCNN) for infrared and visible images fusion in nonsubsampled …
coupled neural network (PCNN) for infrared and visible images fusion in nonsubsampled …
A new contrast based multimodal medical image fusion framework
Medical image fusion plays an important role in clinical applications such as image-guided
surgery, image-guided radiotherapy, noninvasive diagnosis, and treatment planning. The …
surgery, image-guided radiotherapy, noninvasive diagnosis, and treatment planning. The …