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Fall 2017 GRASP Special Seminar: Marc Niethammer, University of North Carolina, “Some Approaches for Deformable Image Registration”

October 6, 2017 @ 3:00 pm - 4:00 pm


Image registration is an important tool in image analysis to spatially align pairs of images. In medical image analysis, for example, registrations to a common atlas space are frequently computed for population-based analyses. Image registration approaches typically consist of a suitable model of deformation and a measure of image similarity. Deformation models range from simple affine transformations to general diffeomorphic transformations, allowing for fine-grained local deformations of space. While diffeomorphic transformations are often desired they may be costly to compute. For example, while the large displacement diffeomorphic metric mapping (LDDMM) model results in diffeomorphic transformations it requires the optimization over high-dimensional spaces. Recently there has been a push in the image registration community (both in computer vision and medical image analysis) to learn aspects of these deformations. This talk will focus on regression approaches to predict deformations between images rapidly, while guaranteeing smoothness of the resulting transformation. If time permits, some approaches to learn similarity measures as well as to assess uncertainties in image registration will also be discussed.


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Marc Niethammer is an Associate Professor at the University of North Carolina at Chapel Hill with a joint appointment in the Department of Computer Science and with the Biomedical Research Imaging Center (BRIC). 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, shape analysis, and, in particular, image registration.


October 6, 2017
3:00 pm - 4:00 pm
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