[HTML][HTML] Medical image super-resolution for smart healthcare applications: A comprehensive survey
The digital transformation in healthcare, propelled by the integration of deep learning
models and the Internet of Things (IoT), is creating unprecedented opportunities for …
models and the Internet of Things (IoT), is creating unprecedented opportunities for …
Deep learning in magnetic resonance image reconstruction
Magnetic resonance (MR) imaging visualises soft tissue contrast in exquisite detail without
harmful ionising radiation. In this work, we provide a state‐of‐the‐art review on the use of …
harmful ionising radiation. In this work, we provide a state‐of‐the‐art review on the use of …
SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry
Every year, millions of brain magnetic resonance imaging (MRI) scans are acquired in
hospitals across the world. These have the potential to revolutionize our understanding of …
hospitals across the world. These have the potential to revolutionize our understanding of …
Fine perceptive gans for brain mr image super-resolution in wavelet domain
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 …
However, limited by factors such as imaging hardware, scanning time, and cost, it is …
Bidirectional mapping generative adversarial networks for brain MR to PET synthesis
Fusing multi-modality medical images, such as magnetic resonance (MR) imaging and
positron emission tomography (PET), can provide various anatomical and functional …
positron emission tomography (PET), can provide various anatomical and functional …
Transformer-empowered multi-scale contextual matching and aggregation for multi-contrast MRI super-resolution
Magnetic resonance imaging (MRI) can present multi-contrast images of the same
anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared …
anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared …
Region-focused multi-view transformer-based generative adversarial network for cardiac cine MRI reconstruction
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 …
and temporal resolution trade-offs. Temporal correlation in cardiac cine MRI is informative …
Multimodal multi-head convolutional attention with various kernel sizes for medical image super-resolution
Super-resolving medical images can help physicians in providing more accurate
diagnostics. In many situations, computed tomography (CT) or magnetic resonance imaging …
diagnostics. In many situations, computed tomography (CT) or magnetic resonance imaging …
Multi-contrast MRI super-resolution via a multi-stage integration network
Super-resolution (SR) plays a crucial role in improving the image quality of magnetic
resonance imaging (MRI). MRI produces multi-contrast images and can provide a clear …
resonance imaging (MRI). MRI produces multi-contrast images and can provide a clear …
Multimodal transformer for accelerated MR imaging
Accelerated multi-modal magnetic resonance (MR) imaging is a new and effective solution
for fast MR imaging, providing superior performance in restoring the target modality from its …
for fast MR imaging, providing superior performance in restoring the target modality from its …