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 …
Multimodal medical image fusion algorithm in the era of big data
In image-based medical decision-making, different modalities of medical images of a given
organ of a patient are captured. Each of these images will represent a modality that will …
organ of a patient are captured. Each of these images will represent a modality that will …
SwinFusion: Cross-domain long-range learning for general image fusion via swin transformer
This study proposes a novel general image fusion framework based on cross-domain long-
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …
[HTML][HTML] Medical image fusion method by deep learning
Y Li, J Zhao, Z Lv, J Li - International Journal of Cognitive Computing in …, 2021 - Elsevier
Deep learning technology has been extensively explored in pattern recognition and image
processing areas. A multi-mode medical image fusion with deep learning will be proposed …
processing areas. A multi-mode medical image fusion with deep learning will be proposed …
EMFusion: An unsupervised enhanced medical image fusion network
Existing image fusion methods always use the same representations for different modal
medical images. Otherwise, they solve the fusion problem by subjectively defining …
medical images. Otherwise, they solve the fusion problem by subjectively defining …
Multimodal medical image fusion based on joint bilateral filter and local gradient energy
X Li, F Zhou, H Tan, W Zhang, C Zhao - Information Sciences, 2021 - Elsevier
As a powerful assistance technique for biomedical diagnosis, multimodal medical image
fusion has emerged as a hot topic in recent years. Unfortunately, the trade-off among fusion …
fusion has emerged as a hot topic in recent years. Unfortunately, the trade-off among fusion …
Coconet: Coupled contrastive learning network with multi-level feature ensemble for multi-modality image fusion
Infrared and visible image fusion targets to provide an informative image by combining
complementary information from different sensors. Existing learning-based fusion …
complementary information from different sensors. Existing learning-based fusion …
Agent architecture of an intelligent medical system based on federated learning and blockchain technology
D Połap, G Srivastava, K Yu - Journal of Information Security and …, 2021 - Elsevier
Multi-agent systems enable the division of complicated tasks into individual objects that can
cooperate. Such architecture can be useful in building solutions in the Internet of Medical …
cooperate. Such architecture can be useful in building solutions in the Internet of Medical …
A bilevel integrated model with data-driven layer ensemble for multi-modality image fusion
Image fusion plays a critical role in a variety of vision and learning applications. Current
fusion approaches are designed to characterize source images, focusing on a certain type of …
fusion approaches are designed to characterize source images, focusing on a certain type of …
SGFusion: A saliency guided deep-learning framework for pixel-level image fusion
Pixel-level image fusion, which merges different modal images into an informative image,
has attracted more and more attention. Despite many methods that have been proposed for …
has attracted more and more attention. Despite many methods that have been proposed for …