Deformable image registration (DIR), aiming to find spatial correspondence between
images, is one of the most critical problems in the domain of medical image analysis. In this …

In deformable registration, the Riemannian framework–Large Deformation Diffeomorphic
Metric Mapping, or LDDMM for short–has inspired numerous techniques for comparing …

We present formulations and numerical algorithms for solving diffeomorphic shape matching
problems. We formulate shape matching as a variational problem governed by a dynamical …

Let D be a dataset of smooth 3D surfaces, partitioned into disjoint classes CL j, j= 1,…, k. We
show how optimized diffeomorphic registration applied to large numbers of pairs (S, S′), S …

The main contribution of this thesis concerns two larger mathematical topics. As a first topic,
we study the geodesic and spline interpolation of images in the framework of the …

In this thesis three diffeomorphic image registration methods are proposed. A Discretize-
then-Optimize approach is used to derive these methods from optimal control formulations in …

We present our work on scalable, GPU-accelerated algorithms for diffeomorphic image
registration. The associated software package is termed CLAIRE. Image registration is a …