Dr. Sung’s primary research focuses on the development of novel medical imaging methods and artificial intelligence using magnetic resonance imaging (MRI). He received a Ph.D. degree in Electrical Engineering from the University of Southern California, Los Angeles, in 2008, and from 2008 to 2012, he finished his postdoctoral training at Stanford in the Departments of Radiology. He joined the University of California, Los Angeles (UCLA) Department of Radiological Sciences, in 2012. His research interest is to develop fast and reliable MRI techniques that can provide improved diagnostic contrast and useful information. In particular, his research group (https://mrrl.ucla.edu/sunglab/) is currently focused on developing advanced deep learning algorithms and quantitative MRI techniques for early diagnosis, treatment guidance, and therapeutic response assessment for oncologic applications. Such developments can offer more robust and reproducible measures of biologic markers associated with human cancers.
Sharmila Majumdar, UCSF
Matthew Lungren, Stanford
The use of Artificial Intelligence (AI) in diagnostic medical imaging is undergoing extensive evaluation. AI has shown impressive accuracy and sensitivity in the identification of imaging abnormalities and promises to enhance tissue-based detection and characterization. This track will explore technical advancements in clinical machine learning and use cases in radiology.