Large Diffeomorphic Deformations Based Indirect Image Registration with Extension to Spatiotemporal Medical Imaging

Release:2017-11-01 Viewed:13


Lecture


ThemeLarge Diffeomorphic Deformations Based Indirect Image Registration with Extension to Spatiotemporal Medical Imaging


Time & Place: Nov 3 2017 14:00 7th classroom


LecturerChong Chen (Chinese Academy of Sciences)


Abstract: In this talk, we adapt the large deformation diffeomorphic metric mapping framework for image registration to the indirect setting, where a template is registered against a target that is given through indirect noisy observations. The registration uses diffeomorphisms that transform the template through a (group) action. These diffeomorphisms are generated by solving a flow equation that is defined by a velocity field with certain regularity. The theoretical analysis includes a proof that indirect image registration has solutions (existence) that are stable and that converge as the data error tends so zero, so it becomes a well-defined regularization method. Moreover, an efficiently computational method is also presented. The talk concludes with examples of indirect image registration in 2D tomography with very sparse and/or highly noisy data and the potential extension to spatiotemporal medical imaging.


InviterChunlin Wu