| Accelerating magnetic resonance imaging via deep learning S Wang, Z Su, L Ying, X Peng, S Zhu, F Liang, D Feng, D Liang 2016 IEEE 13th international symposium on biomedical imaging (ISBI), 514-517, 2016 | 970 | 2016 |
| Accelerating SENSE using compressed sensing D Liang, B Liu, J Wang, L Ying Magnetic Resonance in Medicine: An Official Journal of the International …, 2009 | 549 | 2009 |
| Deep magnetic resonance image reconstruction: Inverse problems meet neural networks D Liang, J Cheng, Z Ke, L Ying IEEE Signal Processing Magazine 37 (1), 141-151, 2020 | 296 | 2020 |
| Deep learning vs. radiomics for predicting axillary lymph node metastasis of breast cancer using ultrasound images: don't forget the peritumoral region Q Sun, X Lin, Y Zhao, L Li, K Yan, D Liang, D Sun, ZC Li Frontiers in oncology 10, 53, 2020 | 201 | 2020 |
| 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, D Liang Magnetic resonance imaging 68, 136-147, 2020 | 183 | 2020 |
| Healthy aging: an automatic analysis of global and regional morphological alterations of human brain X Long, W Liao, C Jiang, D Liang, B Qiu, L Zhang Academic radiology 19 (7), 785-793, 2012 | 151 | 2012 |
| Motion tracking of the carotid artery wall from ultrasound image sequences: a nonlinear state-space approach Z Gao, Y Li, Y Sun, J Yang, H Xiong, H Zhang, X Liu, W Wu, D Liang, S Li IEEE transactions on medical imaging 37 (1), 273-283, 2017 | 139 | 2017 |
| A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification J Zhang, B Zheng, A Gao, X Feng, D Liang, X Long Magnetic Resonance Imaging 78, 119-126, 2021 | 130 | 2021 |
| k‐t ISD: Dynamic cardiac MR imaging using compressed sensing with iterative support detection D Liang, EVR DiBella, RR Chen, L Ying Magnetic resonance in medicine 68 (1), 41-53, 2012 | 121 | 2012 |
| DIMENSION: dynamic MR imaging with both k‐space and spatial prior knowledge obtained via multi‐supervised network training S Wang, Z Ke, H Cheng, S Jia, L Ying, H Zheng, D Liang NMR in Biomedicine 35 (4), e4131, 2022 | 120 | 2022 |
| 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 | 115 | 2013 |
| Nonlinear GRAPPA: A kernel approach to parallel MRI reconstruction Y Chang, D Liang, L Ying Magnetic Resonance in Medicine 68 (3), 730-740, 2012 | 109 | 2012 |
| Sensitivity encoding reconstruction with nonlocal total variation regularization D Liang, H Wang, Y Chang, L Ying Magnetic resonance in medicine 65 (5), 1384-1392, 2011 | 108 | 2011 |
| A kernel-based low-rank (KLR) model for low-dimensional manifold recovery in highly accelerated dynamic MRI U Nakarmi, Y Wang, J Lyu, D Liang, L Ying IEEE transactions on medical imaging 36 (11), 2297-2307, 2017 | 99 | 2017 |
| A facial expression recognition system based on supervised locally linear embedding D Liang, J Yang, Z Zheng, Y Chang Pattern Recognition Letters 26 (15), 2374-2389, 2005 | 99 | 2005 |
| Artifact correction in low‐dose dental CT imaging using Wasserstein generative adversarial networks Z Hu, C Jiang, F Sun, Q Zhang, Y Ge, Y Yang, X Liu, H Zheng, D Liang Medical physics 46 (4), 1686-1696, 2019 | 92 | 2019 |
| Single‐shot T2 mapping using overlapping‐echo detachment planar imaging and a deep convolutional neural network C Cai, C Wang, Y Zeng, S Cai, D Liang, Y Wu, Z Chen, X Ding, J Zhong Magnetic resonance in medicine 80 (5), 2202-2214, 2018 | 91 | 2018 |
| Compressed-sensing photoacoustic computed tomography in vivo with partially known support J Meng, LV Wang, L Ying, D Liang, L Song Optics Express 20 (15), 16510-16523, 2012 | 91 | 2012 |
| Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma ZC Li, H Bai, Q Sun, Y Zhao, Y Lv, J Zhou, C Liang, Y Chen, D Liang, ... Cancer medicine 7 (12), 5999-6009, 2018 | 90 | 2018 |
| DPIR-Net: Direct PET image reconstruction based on the Wasserstein generative adversarial network Z Hu, H Xue, Q Zhang, J Gao, N Zhang, S Zou, Y Teng, X Liu, Y Yang, ... IEEE Transactions on Radiation and Plasma Medical Sciences 5 (1), 35-43, 2020 | 88 | 2020 |
Leslie YingProfessor of Biomedical Engineering & Electrical Engineering, University at Buffalo在 buffalo.edu 的电子邮件经过验证
