A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics

MA Azam, KB Khan, S Salahuddin, E Rehman… - Computers in biology …, 2022 - Elsevier
Background and objectives Over the past two decades, medical imaging has been
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …

Graph-based semi-supervised learning: A review

Y Chong, Y Ding, Q Yan, S Pan - Neurocomputing, 2020 - Elsevier
Considering the labeled samples may be difficult to obtain because they require human
annotators, special devices, or expensive and slow experiments. Semi-supervised learning …

A phase congruency and local Laplacian energy based multi-modality medical image fusion method in NSCT domain

Z Zhu, M Zheng, G Qi, D Wang, Y Xiang - Ieee Access, 2019 - ieeexplore.ieee.org
Multi-modality image fusion provides more comprehensive and sophisticated information in
modern medical diagnosis, remote sensing, video surveillance, and so on. This paper …

Medical image fusion via convolutional sparsity based morphological component analysis

Y Liu, X Chen, RK Ward… - IEEE Signal Processing …, 2019 - ieeexplore.ieee.org
In this letter, a sparse representation (SR) model named convolutional sparsity based
morphological component analysis (CS-MCA) is introduced for pixel-level medical image …

A bilevel integrated model with data-driven layer ensemble for multi-modality image fusion

R Liu, J Liu, Z Jiang, X Fan, Z Luo - IEEE transactions on image …, 2020 - ieeexplore.ieee.org
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 …

Image dehazing by an artificial image fusion method based on adaptive structure decomposition

M Zheng, G Qi, Z Zhu, Y Li, H Wei… - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Haze can seriously affect the visible and visual quality of outdoor images. As a challenge in
practice, image dehazing techniques are always used to remove haze from the captured …

Co-learning feature fusion maps from PET-CT images of lung cancer

A Kumar, M Fulham, D Feng… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The analysis of multi-modality positron emission tomography and computed tomography
(PET-CT) images for computer-aided diagnosis applications (eg, detection and …

Image fusion using hybrid methods in multimodality medical images

SP Yadav, S Yadav - Medical & Biological Engineering & Computing, 2020 - Springer
An image fusion based on multimodal medical images renders a considerable
enhancement in the quality of fused images. An effective image fusion technique produces …

Infrared and visible image fusion via texture conditional generative adversarial network

Y Yang, J Liu, S Huang, W Wan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper proposes an effective infrared and visible image fusion method based on a
texture conditional generative adversarial network (TC-GAN). The constructed TC-GAN …

Triple adversarial learning and multi-view imaginative reasoning for unsupervised domain adaptation person re-identification

H Li, N Dong, Z Yu, D Tao, G Qi - IEEE Transactions on Circuits …, 2021 - ieeexplore.ieee.org
Due to the importance of practical applications, unsupervised domain adaptation (UDA)
person re-identification (re-ID) has attracted increasing attention. However, most of existing …