| Convolutional neural network for efficient estimation of regional brain strains S Wu, W Zhao, K Ghazi, S Ji Scientific reports 9 (1), 17326, 2019 | 73 | 2019 |
| Instantaneous whole-brain strain estimation in dynamic head impact K Ghazi, S Wu, W Zhao, S Ji Journal of Neurotrauma 38 (8), 1023-1035, 2021 | 64 | 2021 |
| Concussion classification via deep learning using whole-brain white matter fiber strains Y Cai, S Wu, W Zhao, Z Li, Z Wu, S Ji PloS one 13 (5), e0197992, 2018 | 42 | 2018 |
| A network-based response feature matrix as a brain injury metric S Wu, W Zhao, B Rowson, S Rowson, S Ji Biomechanics and modeling in mechanobiology 19, 927-942, 2020 | 38 | 2020 |
| Real-time dynamic simulation for highly accurate spatiotemporal brain deformation from impact S Wu, W Zhao, S Ji Computer methods in applied mechanics and engineering 394, 114913, 2022 | 25 | 2022 |
| Dynamic characteristics of impact-induced brain strain in the corpus callosum S Ji, S Wu, W Zhao Brain Multiphysics 3, 100046, 2022 | 15 | 2022 |
| Instantaneous Brain Strain Estimation for Automotive Head Impacts via Deep Learning S Wu, W Zhao, S Barbat, J Ruan, S Ji SAE Technical Paper, 2022 | 11 | 2022 |
| Approximating subject-specific brain injury models via scaling based on head–brain morphological relationships S Wu, W Zhao, Z Wu, T McAllister, J Hu, S Ji Biomechanics and Modeling in Mechanobiology 22 (1), 159-175, 2023 | 8 | 2023 |
| A level-wise spine registration framework to account for large pose changes Y Cai, S Wu, X Fan, J Olson, L Evans, S Lollis, SK Mirza, KD Paulsen, S Ji International journal of computer assisted radiology and surgery 16 (6), 943-953, 2021 | 7 | 2021 |
| A morphologically individualized deep learning brain injury model N Lin, S Wu, S Ji Journal of Neurotrauma 40 (19-20), 2233-2247, 2023 | 6 | 2023 |
| Effective head impact kinematics to preserve brain strain K Ghazi, S Wu, W Zhao, S Ji Annals of biomedical engineering 49 (10), 2777-2790, 2021 | 4 | 2021 |
| A vertebral level-wise data augmentation scheme for segmentation via deep learning S Wu, Y Cai, X Fan, SK Mirza, KD Paulsen, S Ji Medical Imaging 2021: Image Processing 11596, 1159639, 2021 | 3 | 2021 |
| Efficient generation of pretraining samples for developing a deep learning brain injury model via transfer learning N Lin, S Wu, Z Wu, S Ji Annals of Biomedical Engineering 52 (10), 2726-2740, 2024 | 2 | 2024 |
| Towards Efficient Brain Strain Estimation for Automotive Head Impacts via Transfer Learning S Wu, W Zhao, S Barbat, J Ruan, S Ji IRCOBI Conference Proceedings, 353-354, 2021 | 2 | 2021 |
| Subject-specific head injury models via scaling based on head morphology: initial finding S Wu, W Zhao, Z Wu, JC Ford, LA Flashman, TW McAllister, J Hu, S Ji Proceedings of the 2019 International IRCOBI Conference on the Biomechanics …, 2019 | 2 | 2019 |
| Improving the radiographic image analysis of the classic metaphyseal lesion via conditional diffusion models S Wu, S Kurugol, A Tsai Medical Image Analysis 97, 103284, 2024 | 1 | 2024 |
| Deep generative model of the distal tibial classic metaphyseal lesion in infants: assessment of synthetic images S Wu, S Kurugol, PK Kleinman, K Ecklund, M Walters, SA Connolly, ... Radiology Advances 1 (2), umae018, 2024 | 1 | 2024 |
| Masked Conditional Diffusion Models for Image Analysis with Application to Radiographic Diagnosis of Infant Abuse S Wu, S Kurugol, A Tsai International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 1 | 2023 |
| Identifying Critical Head Impact Time Window using a Pre-trained Neural Network: an Initial Study K Ghazi, C Zhang, S Wu, G Tierney, A Clansey, L Wu, S Ji IRCOBI Conference Proceedings, 218-219, 2021 | 1 | 2021 |
| Towards accounting for intraoperative spine motion: a simulation study of registration between stereovision surfaces WR Warner, X Fan, RB Duke, KL Chen, H Stoner, C Li, S Wu, S Ji, ... Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and …, 2023 | | 2023 |
