Stanford University
Showing 341-360 of 684 Results
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Margaret Chin-Chin Lin
Clinical Associate Professor, Radiology
BioDr. Margaret Lin is a board certified radiologist with subspecialty training in thoracic and cardiovascular imaging. Dr. Lin specializes in diseases affecting the lungs and airways, including cancer, infection, and interstitial and inhalational lung diseases. Dr. Lin has a passion for resident education and development of curricula and new educational tools. She is the current Program Director for the Diagnostic Radiology Residency Program.
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Jafi Alyssa Lipson
Current Research and Scholarly InterestsDr. Lipson's research interests include breast density and breast cancer risk assessment; informatics applications in breast imaging; early breast cancer detection and extent of disease evaluation using contrast enhanced mammography, digital breast tomosynthesis, and high resolution breast MRI; novel blood and imaging biomarkers of breast cancer burden and neoadjuvant treatment response; and image-guided wireless localization techniques for breast surgery.
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Dr. Don Listwin
Adjunct Professor, Rad/Precision Health and Integrated Diagnostics
BioDon Listwin is Founder of the Canary Foundation which is dedicated to research in the field of early detection of cancer. Together with Dr. Sanjiv (Sam) Ghambir, they created and built the Canary Center @ Stanford. Don can be reached at: dj22listwin@canaryfoundation.org
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Yongkai Liu
Instructor, Radiology
BioDr. Yongkai Liu is an instructor in the Department of Radiology, Division of Neuroimaging and Neurointervention at Stanford University. His research focuses on developing and evaluating advanced techniques to improve treatment decision-making and prognostication in brain diseases—particularly stroke—using imaging and deep learning. Dr. Liu is a recipient of the prestigious K99/R00 award for his work on integrating large language models with imaging-based deep learning for stroke outcome prediction.
Prior to joining Stanford, Dr. Liu earned his Ph.D. in Physics and Biology in Medicine from UCLA under the mentorship of Prof. Kyung Sung. This rigorous training equipped him with a strong foundation in medicine, deep learning, and physics. His Ph.D. thesis, titled “Advancing Segmentation and Classification Methods in Magnetic Resonance Imaging via Artificial Intelligence,” focused on developing cutting-edge deep learning and machine learning techniques for MRI-based clinical applications. During his master’s studies, he conducted research on CT Virtual Colonoscopy under the guidance of Prof. Jerome Liang, an IEEE Fellow.
Dr. Liu has also made significant contributions to the academic community as a peer reviewer for leading journals, including The Lancet Digital Health, NPJ Digital Medicine, Medical Image Analysis, Medical Physics, Scientific Reports, British Journal of Radiology, BJR|Artificial Intelligence, Annals of Clinical and Translational Neurology, IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Radiation and Plasma Medical Sciences, IEEE Transactions on Biomedical Engineering, and IEEE Transactions on Neural Networks and Learning Systems.
Dr. Liu is an emerging leader in neuroimaging, stroke research, and artificial intelligence. His work has earned wide recognition, including the K99/R00 Award, the 2024 AJNR Lucien Levy Award, the David M. Yousem Research Fellow Award in both 2024 and 2025, and selection as a semi-finalist for the 2024 Cornelius G. Dyke Award. These honors underscore his promise as an investigator and his potential to make significant contributions to the field (https://med.stanford.edu/rsl/news/yongkai-liu-receives-research-fellow-award.html). His research has also been featured in Neurology Today, including his early work linking chain-of-thought methods with clinical reasoning to help advance the use of large language models in real-world clinical care (https://neurologytoday.aan.com/doi/10.1212/netod-blogs.10000031). -
Michael Loecher
Sr Res Engineer, Rad/Radiological Sciences Laboratory
BioMy research focuses primarily on improving methods for measuring flow and motion with MRI. My research interests range from image acquisition and reconstruction to error correction and post processing strategies.
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Andreas Loening
Associate Professor of Radiology (Body MRI)
Current Research and Scholarly InterestsMy lab focuses on expanding the capability of MR and PET/MR as it relates to applications in body imaging. Clinical research aims include the application of new or improved MR sequences to increase the speed, robustness, and diagnostic capability of body MR. Translation research aims include exploring new MR contrast mechanisms and contrast agents, such as for the stratification of cancer within the prostate and the evaluation of the lymphatic system.
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John D. Louie, MD
Clinical Professor, Radiology
Current Research and Scholarly InterestsMy research interests focus on interventional oncology which include radioembolization (SIR Spheres and Theraspheres), chemoembolization, and ablation.
