Medical image super-resolution reconstruction algorithms based on deep learning: A survey

D Qiu, Y Cheng, X Wang - Computer Methods and Programs in …, 2023 - Elsevier
Background and objective With the high-resolution (HR) requirements of medical images in
clinical practice, super-resolution (SR) reconstruction algorithms based on low-resolution …

Review and prospect: artificial intelligence in advanced medical imaging

S Wang, G Cao, Y Wang, S Liao, Q Wang, J Shi… - Frontiers in …, 2021 - frontiersin.org
Artificial intelligence (AI) as an emerging technology is gaining momentum in medical
imaging. Recently, deep learning-based AI techniques have been actively investigated in …

DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution

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 …

Multimodal transformer for accelerated MR imaging

CM Feng, Y Yan, G Chen, Y Xu, Y Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

Deep learning for fast MR imaging: A review for learning reconstruction from incomplete k-space data

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 …

[HTML][HTML] 深度学习在医学影像中的应用综述

施俊, 汪琳琳, 王珊珊, 陈艳霞, 王乾, 魏冬铭, 梁淑君… - 2020 - cjig.cn
摘要深度学习能自动从大样本数据中学习获得优良的特征表达, 有效提升各种机器学习任务的
性能, 已广泛应用于信号处理, 计算机视觉和自然语言处理等诸多领域. 基于深度学习的医学影像 …

A review of deep learning methods for compressed sensing image reconstruction and its medical applications

Y Xie, Q Li - Electronics, 2022 - mdpi.com
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 …

DONet: dual-octave network for fast MR image reconstruction

CM Feng, Z Yang, H Fu, Y Xu, J Yang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …

Parameter-transferred Wasserstein generative adversarial network (PT-WGAN) for low-dose PET image denoising

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 …

Dual-octave convolution for accelerated parallel MR image reconstruction

CM Feng, Z Yang, G Chen, Y Xu, L Shao - Proceedings of the AAAI …, 2021 - ojs.aaai.org
Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose
acceleration by obtaining multiple undersampled images simultaneously through parallel …