The digital transformation in healthcare, propelled by the integration of deep learning
models and the Internet of Things (IoT), is creating unprecedented opportunities for …

With Artificial Intelligence (AI) increasingly permeating various aspects of society, including
healthcare, the adoption of the Transformers neural network architecture is rapidly changing …

Cardiac cine magnetic resonance imaging (MRI) reconstruction is challenging due to spatial
and temporal resolution trade-offs. Temporal correlation in cardiac cine MRI is informative …

Recently, several methods have explored the potential of multi-contrast magnetic resonance
imaging (MRI) super-resolution (SR) and obtain results superior to single-contrast SR …

Video super-resolution techniques aim to obtain high-resolution equivalents of existing low-
resolution videos through a series of operations. In recent research, transformers have been …

Magnetic resonance images (MRI) acquired with low through-plane resolution compromise
time and cost. The poor resolution in one orientation is insufficient to meet the requirement of …

Recently diffusion models (DM) have been applied in magnetic resonance imaging (MRI)
super-resolution (SR) reconstruction exhibiting impressive performance especially with …

Recently, low-field magnetic resonance imaging (MRI) has gained renewed interest to
promote MRI accessibility and affordability worldwide. The presented M4Raw dataset aims …

The cartoon style transfer has attracted widespread attention. Although many researchers
have proposed various methods to develop this field, there are still two areas for …

Super-resolving the magnetic resonance (MR) image of a target contrast under the guidance
of the corresponding auxiliary contrast, which provides additional anatomical information, is …