My scientific pursuits have culminated in a passion for developing computer-aided tools to complement and support the radiologists’ diagnosis and decision-making. Artificial intelligence (AI) techniques will support more efficient and accurate diagnoses and better treatment options. However, the differences in MRI image acquisitions due to manufacturers, field strengths, patient motion, coil and imaging parameters lead to inconsistent appearance and quality of MRI images. These differences pose significant challenges for current machine learning algorithms, leading to reduced accuracy and precision of image interpretation. To solve this challenge, it is necessary to optimize and standardize the pre-processing of images (i.e. inhomogeneity correction, signal normalization, registration to standard template, geometry distortion correction) to reduce the variability of images across centers and scanners. Over the last two decades, I have been working on MRI signal computer simulation, magnetic field estimation, sequence optimization, artifact reduction. Learn More
medical image processing and analysis
Assistant Professor, UC Department of Pediatrics
Yale School of Medicine
Doctor of Philosophy (Ph.D.)
Physics, Institute of Physics Chinese Academy of Sciences, China, 1996.
Master of Science (M.S.)
Physics, Peking University, China, 1991.
Bachelor of Science (B.S)
Physics, Jiling University, China, 1986.