Speaker Profile
M.D., Professor, University of Maryland School of Medicine
Biography
Thorsten Fleiter is a member of the radiology team at the Nation’s first and only integrated Trauma Hospital concentrating on the development of new imaging methods applying AI and robotic techniques to create autonomous systems to shorten the time lost for the detection of life-threatening injuries in severe trauma. The goal of his group is to create less user independent solutions specifically for pre-hospital and remote scenarios to ultimately improve the survival of trauma victims. He led the development of novel imaging methods for ultrasound and computed tomography primarily for emergency imaging and developed multiple advanced acquisition and visualization methods including 4D-ultassound, virtual bronchoscopy/colonoscopy as well as new tools for precision surgery guidance using novel 3D printing methods for spine, facial bone, and dental applications. His group earned several awards for the advanced visualization and simulation of dynamic processes like blood- and airflow to predict pathophysiological changes of aneurysms and stents.
Talk
Applying AI techniques in Severe Trauma Imaging
Routine sub-millimeter scans of the entire body of trauma victims are typically producing 3000-5000 images that must be reviewed instantaneously to detect life threatening injuries. New AI image analysis tools and workflow alterations to further improve this process and shorten the turnaround times will be discussed in this presentation.
Session Abstract – PMWC 2022 Silicon Valley
Track Chairs:
Sharmila Majumdar, UCSF
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.
Sessions:
- AI Roadmap: Opportunities and Challenges (PANEL)
Session Chair: Sean Khozin, CancerLinQ
- Matthew Lungren, AWS
- Patrick Loerch, Gilead
- Greg Yap, Menlo Ventures
- Lydia The, McKinsey & Company
- Chris Gibson, Recursion
- Andrea Mazzocchi, Known Medicine - Actionable AI: Empowering the Stewards of Precision Medicine
- Martin Stumpe, Tempus - Technical Advancements in Clinical Machine Learning - What's New in 2022 (PANEL)
Session Chair: Sharmila Majumdar, UCSF
- Matthew Lungren, AWS - Jayashree Kalpathy-Cramer, Harvard
- John Mongan, UCSF - Image Applications for Clinical Diagnosis
Session Chair: Esther L. Yuh, UCSF
- Thorsten Fleiter, U. of Maryland
- Imon Banerjee, Mayo Clinic
- Pratik Mukherjee, UCSF
- Lawrence Schwartz, Columbia University Medical Center
- Rakesh Shiradkar, Case Western Reserve University - The Impact of AI and High-Resolution Digital Slide Imaging
Session Chair: Ryan Davis, Epredia
- Andy Moye, Paige
- Thomas Westerling-Bui, Aiforia
Session Chair: Fatemeh Zabihollahy, UCLA
- Mirabela Rusu, Stanford
- Mona Flores, NVIDIA
- Kilian Koepsell, Caption Health
- Eric Horler, AIQ Solutions
