Hybrid Deformable Modeling Methods for Reconstruction, Segmentation, Tracking and Classification – Dimitris Metaxas (Rutgers)

When:
July 14, 2010 all-day
2010-07-14T00:00:00-04:00
2010-07-15T00:00:00-04:00

Abstract
Recent advances in deformable models have lead to new classes of methods that borrow the best features form level sets as well as traditional parametric deformable models. In the first part of the course I will present a new class of such models termed Metamorphs whose formulation integrates shape, intensity and texture by borrowing ideas from level sets and traditional parametric deformable models. Further extensions to these models include the inclusion of shape and texture priors. These new models can be used in medical segmentation and registration where organ boundaries are fuzzy and with no assumptions on the noise distribution. Applications include cancer and cardiac detection and reconstruction. In the second part of the talk I will present a real time system for facial and body movement analysis that can be used in ASL recognition, deception and other homeland security applications. Finally, I will highlight some new developments in sparsity theory and their applications to segmentation, sparse learning and medical imaging.
Biography
Dr. Dimitris Metaxas is a Professor II (Distinguished) in the Computer Science Department at Rutgers. He got his PhD in 1992 from the University of Toronto and was on the faculty at UPENN from 1992 to 2002. He is currently directing the Center for Computational Biomedicine, Imaging and Modeling (CBIM). Dr. Metaxas has been conducting research towards the development of formal methods upon which both computer vision, computer graphics and medical imaging can advance synergistically, as well as on massive data analytics problems. In computer vision, he works on the simultaneous segmentation and fitting of complex objects, shape representation, deterministic and statistical object tracking, learning, ASL and human activity recognition. In medical image analysis, he works on segmentation, registration and classification methods for cardiac and cancer applications. In computer graphics he is working on physics-based special effects methods for animation. He has pioneered the use of Navier-Stokes methods for fluid animations that were used in the Movie “Antz” in 1998 by his student Nick Foster. Dr. Metaxas has published over 350 research articles in these areas and has graduated 29 PhD students. His research has been funded by NSF, NIH, ONR, DARPA, AFOSR and the ARO. He is on the Editorial Board of Medical Imaging, an Associate Editor of GMOD, and CAD. Dr. Metaxas received several best paper awards for his work on in the above areas. He is an ONR YIP and a Fellow of the American Institute of Medical and Biological Engineers. He has been a Program Chair of ICCV 2007, a General Chair of MICCAI 2008 and will be a General Chair of ICCV 2011.

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