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
2/14/21: Research by Jean-Emmanuel Bibault and Lei Xing on using deep learning to predict cancer prevalence from satellite images was highlighted by the popular newspaper Le Figaro in a beautifully-titled article, "When Man’s Health is Assessed from Space." Read it here (in French)!
11/10/20: Xing Lab research was recently featured in Stanford's Bio-X News! Notably, our broadly applicable data-driven algorithm for dimensionality reduction was published in Nature Biomedical Engineering.
11/1/20: The 2020 ASTRO Program Committee has selected our abstract titled "Dual-energy CT Imaging Using a Single-energy CT Data via Deep Learning: A Contrast-enhanced CT Study" for Best of ASTRO. Congratulations to Wei Zhao, Tianling Lv, Yang Chen and Lei Xing!
10/1/20: Our work on using AI to guide colorectal cancer care decision has been featured in Stanford Medicine and Bio-X news!
9/17/20: A new book edited by Lei Xing, Maryellen L. Giger, and James K. Min titled Artificial Intelligence in Medicine: Technical Basis and Clinical Applications has been published and is now available for purchase on Amazon.