Accelerated high-dimensional MR imaging with sparse sampling using low-rank tensors J He, Q Liu, A Christodoulou, C Ma, F Lam, ZP Liang
IEEE TMI, 2016
173 2016 X-net: Brain stroke lesion segmentation based on depthwise separable convolution and long-range dependencies K Qi, H Yang, C Li, Z Liu, M Wang, Q Liu, S Wang
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
168 2019 A radiomics approach with CNN for shear-wave elastography breast tumor classification Y Zhou, J Xu, Q Liu, C Li, Z Liu, M Wang, H Zheng, S Wang
IEEE Transactions on Biomedical Engineering 65 (9), 1935-1942, 2018
154 2018 Adaptive dictionary learning in sparse gradient domain for image recovery Q Liu, S Wang, L Ying, X Peng, Y Zhu, D Liang
IEEE Transactions on Image Processing 22 (12), 4652-4663, 2013
120 2013 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 Control 68, 102579, 2021
95 2021 Highly undersampled magnetic resonance image reconstruction using two-level Bregman method with dictionary updating Q Liu, S Wang, K Yang, J Luo, Y Zhu, D Liang
IEEE Transactions on Medical Imaging 32 (7), 1290-1301, 2013
84 2013 Learning joint-sparse codes for calibration-free parallel MR imaging S Wang, S Tan, Y Gao, Q Liu, L Ying, T Xiao, Y Liu, X Liu, H Zheng, ...
IEEE transactions on medical imaging 37 (1), 251-261, 2017
82 2017 IFR-Net: Iterative feature refinement network for compressed sensing MRI Y Liu, Q Liu, M Zhang, Q Yang, S Wang, D Liang
IEEE Transactions on Computational Imaging 6, 434-446, 2019
74 2019 GcsDecolor: Gradient Correlation Similarity for Efficient Contrast Preserving Decolorization DL Q. Liu, P.X. Liu, W. Xie, Y. Wang
IEEE Trans. Image Process., 24 (9), 2889-2904, 2015
71 2015 Multi-view mammographic density classification by dilated and attention-guided residual learning C Li, J Xu, Q Liu, Y Zhou, L Mou, Z Pu, Y Xia, H Zheng, S Wang
IEEE/ACM transactions on computational biology and bioinformatics 18 (3 …, 2020
70 2020 Highly undersampled magnetic resonance imaging reconstruction using autoencoding priors Q Liu, Q Yang, H Cheng, S Wang, M Zhang, D Liang
Magnetic resonance in medicine 83 (1), 322-336, 2020
69 2020 Dictionary learning based impulse noise removal via L1–L1 minimization S Wang, Q Liu, Y Xia, P Dong, J Luo, Q Huang, DD Feng
Signal Processing 93 (9), 2696-2708, 2013
66 2013 Wavelet-improved score-based generative model for medical imaging W Wu, Y Wang, Q Liu, G Wang, J Zhang
IEEE transactions on medical imaging, 2023
61 2023 PANDA‐ Y Zhu, Q Zhang, Q Liu, YXJ Wang, X Liu, H Zheng, D Liang, J Yuan
Magnetic resonance in medicine 73 (1), 263-272, 2015
60 2015 Reconstruction of magnetic resonance imaging by three‐dimensional dual‐dictionary learning Y Song, Z Zhu, Y Lu, Q Liu, J Zhao
Magnetic resonance in medicine 71 (3), 1285-1298, 2014
58 2014 Self-supervised learning for mri reconstruction with a parallel network training framework C Hu, C Li, H Wang, Q Liu, H Zheng, S Wang
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
55 2021 Variable augmented neural network for decolorization and multi-exposure fusion Q Liu, H Leung
Information Fusion 46, 114-127, 2019
55 2019 Gabor feature based nonlocal means filter for textured image denoising S Wang, Y Xia, Q Liu, J Luo, Y Zhu, DD Feng
Journal of Visual Communication and Image Representation 23 (7), 1008-1018, 2012
54 2012 A comparative study of CNN-based super-resolution methods in MRI reconstruction and its beyond W Zeng, J Peng, S Wang, Q Liu
Signal Processing: Image Communication 81, 115701, 2020
52 2020 MRI denoising using progressively distribution-based neural network S Li, J Zhou, D Liang, Q Liu
Magnetic resonance imaging 71, 55-68, 2020
49 2020 
Shanshan WangProfessor of Paul C Lauterbur Research Center,Shenzhen Institute of Advanced Technology, CASE-mail megerősítve itt: siat.ac.cn