The goal of the Deep Biomedical Imaging Laboratory is to develop novel AI-aided analytical and computational tools to enhance the role of quantitative imaging in cancer treatment and to improve the accuracy and precision of radiation therapy.
quantitative imaging will play a leading role in a new era of personalized medicine where quantitative methods of engineering and system sciences have a critical role in disease detection, diagnostics, and treatment;
artificial intelligence (AI), especially deep learning, takes advantage of increased exposure to large and new data sets, has the ability to improve and learn with experience, and will improve the accuracy and efficiency of current medical imaging;
combining the latest quantitative imaging with the cutting-edge AI algorithms can empower clinicians to improve current clinical practice and patient care, especially for those with less experience or limited resources.
Xiaofeng Yang, PhD, DABR is a medical physicist and a professor of Radiation and Cellular Oncology at University of Chicago.
