| Low rank and structured modeling of high-dimensional vector autoregressions S Basu, X Li, G Michailidis IEEE Transactions on Signal Processing 67 (5), 1207-1222, 2019 | 90 | 2019 |
| An integrable equation with nonsmooth solitons Z Qiao, X Li Theoretical and Mathematical Physics 167, 584-589, 2011 | 65 | 2011 |
| Super-resolution whole-brain 3D MR spectroscopic imaging for mapping d-2-hydroxyglutarate and tumor metabolism in isocitrate dehydrogenase 1–mutated human gliomas X Li, B Strasser, K Jafari-Khouzani, B Thapa, J Small, DP Cahill, J Dietrich, ... Radiology 294 (3), 589-597, 2020 | 34 | 2020 |
| A comprehensive review of generative AI in healthcare Y Shokrollahi, S Yarmohammadtoosky, MM Nikahd, P Dong, X Li, L Gu arXiv preprint arXiv:2310.00795, 2023 | 20 | 2023 |
| An integrated inverse space sparse representation framework for tumor classification X Yang, W Wu, Y Chen, X Li, J Zhang, D Long, L Yang Pattern Recognition 93, 293-311, 2019 | 18 | 2019 |
| Seunet-trans: A simple yet effective unet-transformer model for medical image segmentation TH Pham, X Li, KD Nguyen IEEE Access, 2024 | 8 | 2024 |
| Deep learning super-resolution magnetic resonance spectroscopic imaging of brain metabolism and mutant isocitrate dehydrogenase glioma X Li, B Strasser, U Neuberger, P Vollmuth, M Bendszus, W Wick, ... Neuro-oncology advances 4 (1), vdac071, 2022 | 8 | 2022 |
| Improving D‐2‐hydroxyglutarate MR spectroscopic imaging in mutant isocitrate dehydrogenase glioma patients with multiplexed RF‐receive/B0‐shim array coils at … B Strasser, NS Arango, JP Stockmann, B Gagoski, B Thapa, X Li, ... NMR in Biomedicine 35 (1), e4621, 2022 | 6 | 2022 |
| Conductivity map from scanning tunneling potentiometry H Zhang, X Li, Y Chen, C Durand, APL Li, XG Zhang Review of Scientific Instruments 87 (8), 2016 | 6 | 2016 |
| Iterative sparse maximum likelihood-based algorithms with applications to SAR imaging H Abeida, X Li, J Li, MM Al-Harthi International Journal of Remote Sensing Applications 2 (2), 10-23, 2012 | 6 | 2012 |
| Post-processing algorithm for driving conventional scanning tunneling microscope at fast scan rates H Zhang, X Li, Y Chen, J Park, AP Li, X Zhang | 5 | 2017 |
| In Vivo Absolute Metabolite Quantification Using a Multiplexed ERETIC‐RX Array Coil for Whole‐Brain MR Spectroscopic Imaging B Thapa, A Mareyam, J Stockmann, B Strasser, B Keil, P Hoecht, SA Carp, ... Journal of Magnetic Resonance Imaging 56 (1), 121-133, 2022 | 3 | 2022 |
| Deep Learning-based prediction of stress and strain maps in arterial walls for improved cardiovascular risk assessment Y Shokrollahi, P Dong, C Zhou, X Li, L Gu Applied Sciences 14 (1), 379, 2023 | 2 | 2023 |
| Whole-brain high resolution 3D MRSI for measuring 2HG and tumor metabolism in mutant IDH glioma patients B Strasser, B Gagoski, T Bijaya International Society for Magnetic Resonance in Medicine, Montreal 7635, 2019 | 2 | 2019 |
| “Accelerated Bregman Operator Splitting with Backtracking Y Chen, X Li, Y Ouyang, E Pasiliao Inverse problems and Imaging, 2017 | 2 | 2017 |
| Super-resolution 3D MRSI for Mapping 2HG and Tumor Metabolism in Patients with Mutant IDH Glioma X Li, B Strasser, K Jafari-Khouzani, B Thapa, J Small, DP Cahill, J Dietrich, ... | 1 | 2019 |
| Diffusion Models Based Super-Resolution MR Spectroscopic Imaging for Mapping Tumor Metabolism M Alsubaie, X Li, J Dietrich, D Cahill, OC Andronesi ISMRM Workshop on MR Spectroscopy, 2024 | | 2024 |
| Systematic and quantitative testing simulations and theories on phase coarsening by experiments KG Wang, X Li Materialia 37, 102192, 2024 | | 2024 |
| NIMG-16. DEEP LEARNING SUPER-RESOLUTION MR SPECTROSCOPIC IMAGING TO MAP TUMOR METABOLISM IN MUTANT IDH GLIOMA PATIENTS X Li, O Andronesi Neuro-Oncology 23 (Suppl 6), vi131, 2021 | | 2021 |
| BIMG-22. DEEP LEARNING SUPER-RESOLUTION MR SPECTROSCOPIC IMAGING TO MAP TUMOR METABOLISM IN MUTANT IDH GLIOMA PATIENTS X Li, O Andronesi, B Strasser, K Jafari-Khouzani, D Cahill, J Dietrich, ... Neuro-oncology Advances 3 (Suppl 1), i5, 2021 | | 2021 |
