Shuying Li, Ph.D.

Education

• Ph.D., Biomedical Engineering, Washington University in St. Louis, 2023
• M.S., Mechanical Engineering, University of Michigan, 2018
• B.S., Energy and Environmental Systems Engineering, Zhejiang University, 2016

Research Interests

• Computational Biomedical Imaging
• Neurodegenerative Diseases
• Neurophotonics and Biophotonics

Research Bio

My research develops computational tools for biomedical imaging to advance optical imaging, improve diagnosis, deepen biological insight, and support clinical decision-making.

Courses Taught

• CPB 421 Bioethics
• CPB 328 Bioinstrumentation

Publications

As First Author

• Li, S., Malamut, M., McKee, A., Cherry, J.*, & Tian, L.* Age-Informed, Attention-Based Weakly-Supervised Learning for
  Neuropathological Image Assessment. bioRxiv (2025): 2025-05.
• Li, S., Zhang, M., Xue, M., & Zhu, Q. (2024). Real-time breast lesion classification combining diffuse optical tomography frequency domain data and BI-RADS assessment. Journal of Biophotonics, 202300483.
• Zhang, M.†, Li, S. †, Xue, M., & Zhu, Q. (2023), A two-step classification scheme for breast lesion diagnosis using ultrasound-guided diffuse optical tomography and deep learning. Journal of Biomedical Optics, 28(8), 086002-086002.
• Li, S.†, Luo, H.†, Kou, S., Hagemann, I., & Zhu, Q. (2023). Depth-resolved attenuation mapping of human ovary and fallopian tube using optical coherence tomography. Journal of Biophotonics, e202300002.
• Li, S., Zhang, M., Xue, M., & Zhu, Q. (2022). Difference imaging from single measurements in diffuse optical tomography: A deep learning approach. Journal of Biomedical Optics, 27(8), 086003. (Promoted on the SPIE WeChat account)
• Luo, H.†, Li, S.†, Zeng, Y.†, …, Zhu, Q. (2022). Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning. Journal of Biophotonics, e202100349. (Inside cover, top-10 most cited papers among papers published in 2022 in Journal of Biophotonics)
  WashU The Source: https://source.washu.edu/2022/08/pairing-imagin...
• Li, S., Zhang, M., & Zhu, Q. (2021). Ultrasound segmentation-guided edge artifact reduction in diffuse optical tomography using connected component analysis. Biomedical Optics Express, 12(8), 5320-5336.
• Li, S., Huang, K., Zhang, M., Uddin, K. S., & Zhu, Q. (2021). Effect and correction of optode coupling errors in breast imaging using diffuse optical tomography. Biomedical Optics Express, 12(2), 689-704. (Most downloaded papers)
• Li, S.†, Zeng, Y.†, Chapman Jr, W. C. †, Erfanzadeh, M., Nandy, S., Mutch, M., & Zhu, Q. (2020). Adaptive Boosting (AdaBoost)‐based multiwavelength spatial frequency domain imaging and characterization for ex vivo human colorectal tissue assessment. Journal of Biophotonics, 13(6), e201960241. (Inside cover)
  WashU School of Engineering News & Events: https://engineering.wustl.edu/news/2020/Machine...
• Li, S. †, Qin, Y. †, Wang, X., & Yang, X. (2018). Bubble growth in cylindrically-shaped optical absorbers during photo-mediated ultrasound therapy. Physics in Medicine & Biology, 63(12), 125017.

As a Contributing Author

• Luo, H., Nie, H., Lamm, V., Li, S., Thakur, S., Hollander, T., Cho, D., …, & Zhu, Q. In vivo Evaluation of Complex Polyps with Endoscopic Optical Coherence Tomography and Deep Learning during Routine Colonoscopy: A Feasibility Study. (Accepted, Scientific Reports)
• Xue, M., Li, S., & Zhu, Q. (2024). Improving diffuse optical tomography imaging quality using APU-Net: an attention-based physical U-Net model. Journal of Biomedical Optics, 29(8), 086001-086001.
• Xue, M., Zhang, M., Li, S., Zou, Y., & Zhu, Q. (2023). Automated pipeline for breast cancer diagnosis using US assisted diffuse optical tomography. Biomedical Optics Express, 14(11), 6072-6087.
• Luo, H., Li, S., Kou, S., Lin, Y., Hagemann, I. S., & Zhu, Q. (2023). Enhanced 3D visualization of human fallopian tube morphology using a miniature optical coherence tomography catheter. Biomedical Optics Express, 14(7), 3225-3233.
• Zhang, M., Xue, M., Li, S., Zou, Y., & Zhu, Q. (2023). Fusion deep learning approach combining diffuse optical tomography and ultrasound for improving breast cancer classification. Biomedical Optics Express, 14(4), 1636-1646.
• Poplack, S. P., Young, C. A., Hagemann, I. S., Luo, J., Herman, C. R., Wiele, K., Li, S., ... & Zhu, Q. (2021). Prospective assessment of adjunctive ultrasound-guided diffuse optical tomography in women undergoing breast biopsy: Impact on BI-RADS assessments. European journal of radiology, 145, 110029.
• Zhang, M., Li, S., Zou, Y., & Zhu, Q. (2021). Deep learning-based method to accurately estimate breast tissue optical properties in the presence of the chest wall. Journal of Biomedical Optics 26 (10), 106004
• Zou, Y., Zeng, Y., Li, S., & Zhu, Q. (2021). Machine learning model with physical constraints for diffuse optical tomography. Biomedical Optics Express, 12(9), 5720-5735. 
• Zeng, Y., Chapman Jr, W. C., Lin, Y., Li, S., Mutch, M., & Zhu, Q. (2021). Diagnosing colorectal abnormalities using scattering coefficient maps acquired from optical coherence tomography. Journal of biophotonics, 14(1), e202000276.
• Zhang, M., Uddin, K. S., Li, S., & Zhu, Q. (2020). Target depth-regularized reconstruction in diffuse optical tomography using ultrasound segmentation as prior information. Biomedical Optics Express, 11(6), 3331-3345.
• Samanta, S., Jiang, J., Ye, D., Hutchinson, M., Zeng, Y., Li, S., ... & Tai, Y. C. (2020). Point-of-Care PET/Ultrasound Imaging for Detection of Atherosclerotic Vulnerable Plaque: A Feasibility Study. Journal of nuclear medicine 61 (supplement 1), 310-310.
• Zeng, Y., Xu, S., Chapman, W. C., Li, S., Alipour, Z., Abdelal, H., & Chatterjee, D. (2020). Real-time colorectal cancer diagnosis using PR-OCT with deep learning. Theranostics, 10(6), 2587.
• Zeng, Y., Nandy, S., Rao, B., Li, S., Hagemann, A. R., Kuroki, L. K., ... & Zhu, Q. (2019). Histogram analysis of en face scattering coefficient map predicts malignancy in human ovarian tissue. Journal of Biophotonics, 12(11), e201900115.