Artificial intelligence (AI) as an emerging technology is gaining momentum in medical imaging. Recently, deep learning-based AI techniques have been actively investigated in …
S Wang, H Cheng, L Ying, T Xiao, Z Ke, H Zheng… - Magnetic resonance …, 2020 - Elsevier
This paper proposes a multi-channel image reconstruction method, named DeepcomplexMRI, to accelerate parallel MR imaging with residual complex convolutional …
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 …
S Wang, T Xiao, Q Liu, H Zheng - Biomedical Signal Processing and …, 2021 - Elsevier
Magnetic resonance imaging is a powerful imaging modality that can provide versatile information. However, it has a fundamental challenge that is time consuming to acquire …
Compressed sensing (CS) and its medical applications are active areas of research. In this paper, we review recent works using deep learning method to solve CS problem for images …
Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration has long been the subject of research. This is commonly achieved by obtaining …
Y Gong, H Shan, Y Teng, N Tu, M Li… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Due to the widespread of positron emission tomography (PET) in clinical practice, the potential risk of PET-associated radiation dose to patients needs to be minimized. However …
Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration by obtaining multiple undersampled images simultaneously through parallel …