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 | 169 | 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 | 153 | 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 | 96 | 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 | 62 | 2023 |
PANDA‐ : Integrating principal component analysis and dictionary learning for fast mapping 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 | 57 | 2021 |
Variable augmented neural network for decolorization and multi-exposure fusion Q Liu, H Leung Information Fusion 46, 114-127, 2019 | 56 | 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 |