Department of Radiology and Radiological Sciences Presents
17th Annual Pendergrass Grand Rounds Lecture in Thoracic Radiology
"Data Driven AI in Lung Screening CT"
featuring
Bennett Landman, Ph.D.
Professor and Department Chair | Electrical and Computer Engineering (primary), Computer Science, Biomedical Engineering, Radiology and Radiological Sciences, Vanderbilt Brain Institute, Psychiatry and Behavioral Sciences, Biomedical Informatics, Vanderbilt University
Principal Scientist of ImageVU | Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center
Biomarker Core Co-Lead | Vanderbilt Alzheimer's Disease Research Center
March 11, 2022 | Noon - 1 p.m.
Zoom
Register Here
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This grand rounds lecture is designed for faculty, residents, staff and medical students.
Learning objectives of this presentation include:
- Describe emerging AI modeling techniques used in lung screening research.
- Recognize the importance of how imaging context can be used to assist computer interpretation of CT images.
- Summarize challenges in integrating multiple data sources (imaging, prior imaging, medical records) into AI models.
- Discuss approaches for using AI to add value to the lung screening CT workflow.
Learn more about the Pendergrass Lecture in Thoracic Radiology here.
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Bennett A. Landman, Ph.D. 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.
