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GTC DC 2017

DC7130 - The Impact of Deep Learning on Radiology - 2017 Update

Session Speakers
  • Ronald Summers - Senior Investigator, NIH Clinical Center

    Ronald M. Summers received the B.A. degree in physics and the M.D. and Ph.D. degrees in Medicine/Anatomy & Cell Biology from the University of Pennsylvania. He completed a medical internship at the Presbyterian-University of Pennsylvania Hospital, Philadelphia, PA, a radiology residency at the University of Michigan, Ann Arbor, MI, and an MRI fellowship at Duke University, Durham, NC. In 1994, he joined the Diagnostic Radiology Department at the NIH Clinical Center in Bethesda, MD where he is now a tenured Senior Investigator and Staff Radiologist. In 2013, he was named a Fellow of the Society of Abdominal Radiologists. He is currently Chief of the Clinical Image Processing Service and directs the Imaging Biomarkers and Computer-Aided Diagnosis (CAD) Laboratory. In 2000, he received the Presidential Early Career Award for Scientists and Engineers, presented by Dr. Neal Lane, President Clinton's science advisor. In 2012, he received the NIH Director's Award.

Session Description

Major advances in computer science are beginning to have an impact on radiology. The rapid achievements in performance for object detection in natural images have enabled these impacts. There has been an explosion of research interest and number of publications regarding the use of deep learning in radiology. In this presentation, I will show examples of how deep learning has led to major performance improvements in radiology image analysis, including image segmentation and computer aided diagnosis.


Additional Information
Intermediate
AI in Healthcare
Healthcare & Life Sciences
Talk
25 minutes
Session Schedule