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Our Team

Yunxiang Li, PhD

Yunxiang Li, PhD

Education

Education
  • Ph.D. in Biomedical Engineering – Medical Physics Track, University of Texas Southwestern Medical Center, Dallas, TX (2022-2026)
  • B.S. in Computer Science, Hangzhou Dianzi University, China (2018-2022)

Awards & Honors 
  • Distinguished Ph.D. Career Award, Medical Physics Graduate Program, UT Southwestern Medical Center, 2025
  • Student of the Year Award, Medical Physics Graduate Program, UT Southwestern Medical Center, 2024
  • Third place of MICCAI HECKTOR challenge, 2022

Selected Publications and Abstracts

  • Li, Y., Shao, H.-C., Liang, X., Chen, L., Li, R., Jiang, S., Wang, J., & Zhang, Y. (2024). Zero-shot medical image translation via frequency-guided diffusion models. IEEE Transactions on Medical Imaging, vol. 43, no. 3, pp. 980–993, Mar. 2024.

  • Li, Y., Chen, M., Wang, K., Ma, J., Bovik, A. C., & Zhang, Y. (2025). SAMScore: A content structural similarity metric for image translation evaluation. IEEE Transactions on Artificial Intelligence, vol. 6, no. 8, pp. 2027–2040, 2025.

  • Li, Y., Kong, X., Xie, J., Ver Steeg, G., & Zhang, Y. (2025). Denoising diffusion wavelet models for zero-shot medical image translation. Knowledge-Based Systems, vol. 324, 113800, 2025.

  • Li, Y., Li, Z., Zhang, K., Dan, R., Jiang, S., & Zhang, Y. (2023). ChatDoctor: A medical chat model fine-tuned on a large language model Meta-AI (LLaMA) using medical domain knowledge. Cureus, vol. 15, no. 6, e40895, Jun. 2023.

  • Li, Y., Shao, H.-C., Qian, X., & Zhang, Y. (2025). FDDM: Unsupervised medical image translation with a frequency-decoupled diffusion model. Machine Learning: Science and Technology, 2025.

  • Li, Y., Liao, Y.-P., Wang, J., Lu, W., & Zhang, Y. (2025). Patient-specific MRI super-resolution via implicit neural representations and knowledge transfer. Physics in Medicine & Biology, vol. 70, no. 7, 075021, 2025.

  • Li, Y., Deng, J., & Zhang, Y. (2025). Universal mapping and patient-specific prior implicit neural representation for enhanced high-resolution MRI in MRI-guided radiotherapy. Medical Physics, 2025.

  • Li, Y., Liang, X., Xie, J., Deng, J., Lu, W., & Zhang, Y. (2025). A universal medical imaging modality translation model in brain and head-and-neck radiotherapy. Radiotherapy and Oncology, 111321, 2025.

  • Li, Y., Dai, Y., Liao, Y.-P., Deng, J., & Zhang, Y. (2026). Band-limited implicit neural representations for diffusion-weighted imaging denoising. Physics in Medicine and Biology, vol. 71, no. 1, 015033, 2026.

  • Li, Y., Liao, Y.-P., Dai, Y., Deng, J., & Zhang, Y. (2026). Landmark matching and B-spline implicit neural representations for diffusion-weighted imaging distortion correction. Physics in Medicine and Biology, 2026.

  • Li, Y., Zeng, G., Zhang, Y., Wang, J., Jin, Q., Sun, L., Zhang, Q., Lian, Q., Qian, G., Xia, N., Peng, R., Tang, K., Wang, S., & Wang, Y. (2021). AGMB-Transformer: Anatomy-guided multi-branch transformer network for automated evaluation of root canal therapy. IEEE Journal of Biomedical and Health Informatics, 2021.

  • Li, Y., Wang, S., Wang, J., Zeng, G., Liu, W., Zhang, Q., Jin, Q., & Wang, Y. (2021). GT U-Net: A U-Net like group transformer network for tooth root segmentation. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Machine Learning in Medical Imaging (pp. 386–395), 2021.

  • Li, Y., Dan, R., Wang, S., Cao, Y., Luo, X., Tan, C., Jia, G., Zhou, H., Zhang, Y., Wang, Y., & Wang, L. (2022). Plug-and-play shape refinement framework for multi-site and lifespan brain skull stripping. In International Workshop on Machine Learning in Medical Imaging (pp. 81–90), 2022.

  • Dan, R.*, Li, Y.*, Wang, Y., et al. (2023). CDNet: Contrastive disentangled network for fine-grained image categorization of ocular B-scan ultrasound. IEEE Journal of Biomedical and Health Informatics, 2023.

  • Wang, K.*, Li, Y.*, Dohopolski, M., Peng, T., Lu, W., Zhang, Y., & Wang, J. (2022). Recurrence-free survival prediction under the guidance of automatic gross tumor volume segmentation for head and neck cancers. In 3D Head and Neck Tumor Segmentation in PET/CT Challenge (pp. 144–153), 2022.

  • Li, Z., Li, Y., Li, Q., Wang, P., Guo, D., Lu, L., Jin, D., Zhang, Y., & Hong, Q. (2023). LViT: Language meets vision transformer in medical image segmentation. IEEE Transactions on Medical Imaging, vol. 43, no. 1, pp. 96–107, 2023.

  • Shao, H.-C., Li, Y., Wang, J., Jiang, S., & Zhang, Y. (2023). Real-time liver tumor localization via combined surface imaging and a single x-ray projection. Physics in Medicine & Biology, vol. 68, no. 6, 065002, 2023.

  • Shao, H.-C., Li, Y., Wang, J., Jiang, S., & Zhang, Y. (2023). Real-time liver motion estimation via deep learning-based angle-agnostic X-ray imaging. Medical Physics, vol. 50, no. 11, pp. 6649–6662, 2023.

  • Xie, J., Shao, H.-C., Li, Y., & Zhang, Y. (2024). Prior frequency guided diffusion model for limited angle (LA)-CBCT reconstruction. Physics in Medicine & Biology, vol. 69, no. 13, 135008, 2024.

  • Shan, D., Li, Z., Li, Y., Li, Q., Tian, J., & Hong, Q. (2025). STPNet: Scale-aware text prompt network for medical image segmentation. IEEE Transactions on Image Processing, 2025.

Abstracts

  • Li, Y., Shao, H.-C., Liang, X., Chen, L., Li, R., Jiang, S., Wang, J., & Zhang, Y. (2023). CBCT-to-CT synthesis via a CT-domain frequency-guided diffusion model (FGDM). In AAPM 65th Annual Meeting & Exhibition 2023 (Oral). AAPM.

  • Li, Y., Shao, H.-C., & Zhang, Y. (2023). Brain MRI synthesis with controllable tumor inpainting by a segmentation-guided diffusion model (SGDM). In AAPM 65th Annual Meeting & Exhibition 2023. AAPM.

  • Li, Y., Shao, H.-C., Qian, X., & Zhang, Y. (2024). Unsupervised MR-to-CT translation with a frequency-decoupled diffusion model. In 20th International Conference on the Use of Computers in Radiation Therapy (ICCR) 2024 (Oral).

  • Li, Y., Jing, B., Wang, J., & Zhang, Y. (2024). Enhancing nnUNet performance with a plug-and-play segment anything model for few-shot medical image segmentation (nnSAM). In AAPM 66th Annual Meeting & Exhibition 2024. AAPM.

  • Li, Y., & Zhang, Y. (2024). Zero-shot cone-beam computed tomography (CBCT) to CT conversion using a denoising diffusion wavelet model (DDWM). In AAPM 66th Annual Meeting & Exhibition 2024 (Oral). AAPM.

  • Li, Y., Liang, X., Xie, J., Deng, J., Lu, W., & Zhang, Y. (2025). A foundational model for medical imaging modality translation in head and neck radiotherapy. In AAPM 67th Annual Meeting & Exhibition 2025 (Oral). AAPM.

  • Li, Y., & Zhang, Y. (2025). Universal anatomical mapping and patient-specific prior implicit neural representation for MRI super-resolution. In AAPM 67th Annual Meeting & Exhibition 2025. AAPM.

  • Li, Y., Liao, Y.-P., Dai, Y., Deng, J., & Zhang, Y. (2026). Landmark matching and B-spline implicit neural representations for diffusion-weighted imaging distortion correction. In ISMRM 34th Annual Meeting & Exhibition 2026 (Oral). ISMRM.

  • Li, Y., Liao, Y.-P., Dai, Y., Deng, J., & Zhang, Y. (2026). Accurate estimation of intravoxel incoherent motion parameters based on implicit neural representation. In ISMRM 34th Annual Meeting & Exhibition 2026. ISMRM.

Redefining Possible