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

S Wang, T **ao, 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 …

MRI-guidance for motion management in external beam radiotherapy: current status and future challenges

C Paganelli, B Whelan, M Peroni… - Physics in Medicine …, 2018‏ - iopscience.iop.org
High precision conformal radiotherapy requires sophisticated imaging techniques to aid in
target localisation for planning and treatment, particularly when organ motion due to …

Accelerating magnetic resonance imaging via deep learning

S Wang, Z Su, L Ying, X Peng, S Zhu… - 2016 IEEE 13th …, 2016‏ - ieeexplore.ieee.org
This paper proposes a deep learning approach for accelerating magnetic resonance
imaging (MRI) using a large number of existing high quality MR images as the training …

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

S Wang, H Cheng, L Ying, T **ao, 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 …

Fault diagnosis for a wind turbine transmission system based on manifold learning and Shannon wavelet support vector machine

B Tang, T Song, F Li, L Deng - Renewable Energy, 2014‏ - Elsevier
Fault diagnosis for wind turbine transmission systems is an important task for reducing their
maintenance cost. However, the non-stationary dynamic operating conditions of wind …

Direct shape regression networks for end-to-end face alignment

X Miao, X Zhen, X Liu, C Deng… - Proceedings of the …, 2018‏ - openaccess.thecvf.com
Face alignment has been extensively studied in computer vision community due to its
fundamental role in facial analysis, but it remains an unsolved problem. The major …

Segmentation of ultrasound image sequences by combing a novel deep siamese network with a deformable contour model

B Ni, Z Liu, X Cai, M Nappi, S Wan - Neural Computing and Applications, 2023‏ - Springer
Deformable contours are widely applied in medical image segmentation, which are usually
derived from appearance cues in medical images. However, the performance of deformed …

[HTML][HTML] McSTRA: A multi-branch cascaded swin transformer for point spread function-guided robust MRI reconstruction

M Ekanayake, K Pawar, M Harandi, G Egan… - Computers in Biology …, 2024‏ - Elsevier
Deep learning MRI reconstruction methods are often based on Convolutional neural
network (CNN) models; however, they are limited in capturing global correlations among …

Liver 4DMRI: a retrospective image‐based sorting method

C Paganelli, P Summers, M Bellomi, G Baroni… - Medical …, 2015‏ - Wiley Online Library
Purpose: Four‐dimensional magnetic resonance imaging (4DMRI) is an emerging
technique in radiotherapy treatment planning for organ motion quantification. In this paper …

PET respiratory motion correction: quo vadis?

F Lamare, A Bousse, K Thielemans, C Liu… - Physics in Medicine …, 2022‏ - iopscience.iop.org
Positron emission tomography (PET) respiratory motion correction has been a subject of
great interest for the last twenty years, prompted mainly by the development of multimodality …