[HTML][HTML] Deep learning based synthesis of MRI, CT and PET: Review and analysis

S Dayarathna, KT Islam, S Uribe, G Yang, M Hayat… - Medical image …, 2024 - Elsevier
Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …

Generative AI for brain image computing and brain network computing: a review

C Gong, C **g, X Chen, CM Pun, G Huang… - Frontiers in …, 2023 - frontiersin.org
Recent years have witnessed a significant advancement in brain imaging techniques that
offer a non-invasive approach to map** the structure and function of the brain …

Fine perceptive gans for brain mr image super-resolution in wavelet domain

S You, B Lei, S Wang, CK Chui… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Magnetic resonance (MR) imaging plays an important role in clinical and brain exploration.
However, limited by factors such as imaging hardware, scanning time, and cost, it is …

Morphological feature visualization of Alzheimer's disease via multidirectional perception GAN

W Yu, B Lei, S Wang, Y Liu, Z Feng… - … on Neural Networks …, 2022 - ieeexplore.ieee.org
The diagnosis of early stages of Alzheimer's disease (AD) is essential for timely treatment to
slow further deterioration. Visualizing the morphological features for early stages of AD is of …

Conversion between CT and MRI images using diffusion and score-matching models

Q Lyu, G Wang - ar** review
H Ali, MR Biswas, F Mohsen, U Shah, A Alamgir… - Insights into …, 2022 - Springer
The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …

BPGAN: Brain PET synthesis from MRI using generative adversarial network for multi-modal Alzheimer's disease diagnosis

J Zhang, X He, L Qing, F Gao, B Wang - Computer Methods and Programs …, 2022 - Elsevier
Abstract Background and Objective Multi-modal medical images, such as magnetic
resonance imaging (MRI) and positron emission tomography (PET), have been widely used …

Alzheimer's disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions

A Elazab, C Wang, M Abdelaziz, J Zhang, J Gu… - Expert Systems with …, 2024 - Elsevier
Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …

Fractal boundary layer and its basic properties

SJ Kou, CH He, XC Men, JH He - Fractals, 2022 - World Scientific
In this paper, the fractal calculus is introduced to study a non-smooth boundary layer of a
viscous fluid, and a fractal-fractional modification of the Blasius equation is suggested and …

[HTML][HTML] Applications of generative adversarial networks in neuroimaging and clinical neuroscience

R Wang, V Bashyam, Z Yang, F Yu, V Tassopoulou… - Neuroimage, 2023 - Elsevier
Generative adversarial networks (GANs) are one powerful type of deep learning models that
have been successfully utilized in numerous fields. They belong to the broader family of …