"Data driven interference in diffusion MRI: Deep learning harmonization of quantitative brain biomarkers"
The activity is designed to help the learner:
• Describe emerging diffusion MRI modeling techniques used in Alzheimer’s disease research.
• Recognize the importance of how scanning hardware and protocol impact derived diffusion measures.
• Summarize challenges in integrating multi-site diffusion MRI into quantitative analysis.
• Discuss approaches for harmonizing diffusion MRI data in multi-site studies.
About the Speaker:
Bennett A. Landman, PhD, is Professor and Department Chair of Electrical and Computer Engineering at Vanderbilt University, with appointments in Computer Science, Biomedical Engineering, Radiology and Radiological Sciences, Psychiatry and Behavioral Sciences, Biomedical Informatics, and Neurology. He graduated with a bachelor of science (’01) and master of engineering (’02) in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, MA. After graduation, he worked in an image processing startup company and a private medical imaging research firm before returning for a doctorate in biomedical engineering (‘08) from Johns Hopkins University School of Medicine, Baltimore, MD. From 2010 to 2021, he severed on the Faculty of the Electrical Engineering and Computer Science Department, Vanderbilt University, Nashville, TN. In July 2021, he joined and became the first chair of the newly formed Electrical and Computer Engineering Department. His research concentrates on applying image-processing technologies to leverage large-scale imaging studies to improve understanding of individual anatomy and personalize medicine.
Dr. Landman has received grant funding from the National Institutes of Health, the National Science Foundation, the Department of Defense, and industry support. He is highly collaborative with 340+ co-authors across disciplines, career stages, and institutions, resulting in 340+ peer-reviewed publications and 9,500+ citations. He served on the MICCAI Society Challenge Working Group, as co-chair of the SPIE Medical Imaging Image Processing conference (2017-2021), as co-chair of the SIIM Machine Learning Tools Committee (2018-2021), and on the editorial boards of the IEEE Transactions of Medical Imaging (2015-) and SIIM Journal of Digital Imaging. He has organized 11 workshops and challenges at MICCAI since 2011 and has supported challenges with SPIE, ISBI, ISMRM, and Kaggle. He served founding director of the Center for Computational Imaging at the Vanderbilt University Institute of Image Science and as chair of the faculty advisory board of the Vanderbilt University Advanced Computing Center for Research and Education (ACCRE). He is currently the Principal Scientist of ImageVU, Vanderbilt’s clinical data reuse initiative in Radiology.
CME/CE credit for Psychiatry Grand Rounds is only available during the live feed time and for a brief time immediately following. The code for this week's session is displayed at the opening and closing of the meeting and also in the Chair's Office Zoom Account Name during the meeting.
For CME/CE information about this session, please visit:
April 8 Psychiatry Grand Rounds | Bennett Landman, PhD
This talk is sponsored by the
Department of Psychiatry and Behavioral Sciences
This educational activity received no commercial support.