Xing Laboratory

Our vision is to be a premier laboratory of artificial intelligence (AI), biomedical physics, and bioengineering in the world. We are embarking systematic research on various important issues in these fields by combining our strengths in medical physics, engineering, biology, and medicine. The following are a few highlights of our current research focuses:

• Development of novel AI strategies for disease diagnosis, treatment planning, therapeutic guidance, prognosis and outcome assessment
• Deep learning-driven image reconstruction and analysis, as well the clinical implementation of the novel quantitative image processing techniques
• Nanotechnology and molecular/biological imaging for precision medicine
• More details about our research »

An AI paper by Ma M, Kavolchuk N, Buyyounoski M, Xing L, Yang Y entitled “Dosimetric Features-Driven Machine Learning Model for DVHs Prediction in VMAT Treatment Planning” (Med Phys 46, 857-867, 2019. PMID: 30536442) is listed as the Top Download of the Year in Medical Physics! Congrats the team!

The collaborative work on using AI for real-time bladder tumor detection (E. Shkolyar, X. Jia, T.C. Chang, D. Trivedi, K. E. Mach, M. Meng, L. Xing, J. Liao, European Urology 76, 714-718, 2019) won the best video at the 2020 Annual Meeting of American Urological Association (AUA).

Our recent work on using deep learning for CT image reconstruction with only a single projection is published in Nature Biomedical Engineering (Shen L, Zhao W, Xing L, Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning, Nature Biomedical Engineering 3, 880-888, 2019).