Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
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 …
Benchmarking and comparing multi-exposure image fusion algorithms
X Zhang - Information Fusion, 2021 - Elsevier
Multi-exposure image fusion (MEF) is an important area in computer vision and has attracted
increasing interests in recent years. Apart from conventional algorithms, deep learning …
increasing interests in recent years. Apart from conventional algorithms, deep learning …
A novel approach based on grasshopper optimization algorithm for medical image fusion
PH Dinh - Expert Systems with Applications, 2021 - Elsevier
The fusion of multi-modal medical images makes a significant contribution to clinical
diagnosis and analysis because it allows diagnostic imaging practitioners to make a more …
diagnosis and analysis because it allows diagnostic imaging practitioners to make a more …
Multi-modal medical image fusion based on equilibrium optimizer algorithm and local energy functions
PH Dinh - Applied Intelligence, 2021 - Springer
Multi-modal medical image fusion brings many benefits to clinical diagnosis and analysis
because it creates favorable conditions for diagnostic imaging practitioners to make a more …
because it creates favorable conditions for diagnostic imaging practitioners to make a more …
An improved medical image synthesis approach based on marine predators algorithm and maximum gabor energy
PH Dinh - Neural Computing and Applications, 2022 - Springer
Multimodal medical image fusion has been attracting the attention of researchers in recent
years because it supports doctors in enhancing clinical diagnosis. Improving the quality of …
years because it supports doctors in enhancing clinical diagnosis. Improving the quality of …
Combining gabor energy with equilibrium optimizer algorithm for multi-modality medical image fusion
PH Dinh - Biomedical Signal Processing and Control, 2021 - Elsevier
Medical image fusion is a technique of extracting information from multiple image modalities
and combining them to create a single image with the aim of improving the image content …
and combining them to create a single image with the aim of improving the image content …
Combining spectral total variation with dynamic threshold neural P systems for medical image fusion
PH Dinh - Biomedical Signal Processing and Control, 2023 - Elsevier
Synthesis of medical images is one of the indispensable tasks today because of its
applications in clinical diagnosis. Composite images often suffer from problems such as …
applications in clinical diagnosis. Composite images often suffer from problems such as …
Msgfusion: Medical semantic guided two-branch network for multimodal brain image fusion
Multimodal image fusion plays an essential role in medical image analysis and application,
where computed tomography (CT), magnetic resonance (MR), single-photon emission …
where computed tomography (CT), magnetic resonance (MR), single-photon emission …
F-DARTS: Foveated differentiable architecture search based multimodal medical image fusion
S Ye, T Wang, M Ding, X Zhang - IEEE Transactions on Medical …, 2023 - ieeexplore.ieee.org
Multimodal medical image fusion (MMIF) is highly significant in such fields as disease
diagnosis and treatment. The traditional MMIF methods are difficult to provide satisfactory …
diagnosis and treatment. The traditional MMIF methods are difficult to provide satisfactory …