|Time:||July 5, 2021|
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Prof. Marc Niethammer
Department of Computer Science
The University of North Carolina at Chapel Hill
Monday 2021-07-05 16:00
Image registration is an important component for many medical image analysis methods to establish spatial correspondences. Over the last years many deep learning approaches to image registration have been proposed. In this talk, I will give a brief overview of how these deep learning approaches go beyond more classical optimization-based registration approaches and how they allow for more sophisticated formulations. In particular, I will emphasize how these approaches motivate significantly simpler registration formulations and how they can motivate a different way of parameterizing deep neural networks.
Marc Niethammer is a Professor at the University of North Carolina at Chapel Hill in the Department of Computer Science. He received his Ph.D. in Electrical and Computer Engineering from the Georgia Institute of Technology and post-doctoral training at Harvard Medical School/Brigham and Women's Hospital. His research interests lie in the areas of biomedical image analysis focusing on application-driven algorithm design for segmentation, registration, machine learning, and shape analysis.
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