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 comprehensive survey analysis for present solutions of medical image fusion and future directions
OS Faragallah, H El-Hoseny, W El-Shafai… - IEEE …, 2020 - ieeexplore.ieee.org
The track of medical imaging has witnessed several advancements in the last years. Several
medical imaging modalities have appeared in the last decades including X-ray, Computed …
medical imaging modalities have appeared in the last decades including X-ray, Computed …
Transmed: Transformers advance multi-modal medical image classification
Y Dai, Y Gao, F Liu - Diagnostics, 2021 - mdpi.com
Over the past decade, convolutional neural networks (CNN) have shown very competitive
performance in medical image analysis tasks, such as disease classification, tumor …
performance in medical image analysis tasks, such as disease classification, tumor …
Multi-modality medical image fusion technique using multi-objective differential evolution based deep neural networks
The advancements in automated diagnostic tools allow researchers to obtain more and
more information from medical images. Recently, to obtain more informative medical …
more information from medical images. Recently, to obtain more informative medical …
[HTML][HTML] DiCyc: GAN-based deformation invariant cross-domain information fusion for medical image synthesis
Cycle-consistent generative adversarial network (CycleGAN) has been widely used for cross-
domain medical image synthesis tasks particularly due to its ability to deal with unpaired …
domain medical image synthesis tasks particularly due to its ability to deal with unpaired …
Investigating the role of image fusion in brain tumor classification models based on machine learning algorithm for personalized medicine
R Nanmaran, S Srimathi, G Yamuna… - … methods in medicine, 2022 - Wiley Online Library
Image fusion can be performed on images either in spatial domain or frequency domain
methods. Frequency domain methods will be most preferred because these methods can …
methods. Frequency domain methods will be most preferred because these methods can …
Multi-modal brain image fusion based on multi-level edge-preserving filtering
Recently, multi-modal medical imaging technology and its collaborative diagnosis
technology are developing rapidly. The application of medical image fusion technology in …
technology are developing rapidly. The application of medical image fusion technology in …
Remote sensing image defogging networks based on dual self-attention boost residual octave convolution
Z Zhu, Y Luo, G Qi, J Meng, Y Li, N Mazur - Remote Sensing, 2021 - mdpi.com
Remote sensing images have been widely used in military, national defense, disaster
emergency response, ecological environment monitoring, among other applications …
emergency response, ecological environment monitoring, among other applications …
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 via discrete stationary wavelet transform and an enhanced radial basis function neural network
Medical image fusion of images obtained via different modes can expand the inherent
information of original images, whereby the fused image has a superior ability to display …
information of original images, whereby the fused image has a superior ability to display …