Abstract. To achieve sparse parametrizations that allows intuitive analysis, we aim to represent deformation with a basis containing interpretable elements, and we wish to use elements that have the description capacity to represent the deformation compactly. To accomplish this, we introduce in this paper higher-order momentum distributions in the LDDMM registration framework. While the zeroth ...

Computing a template in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework is a key step for the study of large databases of anatomical surfaces, but can lead to very computationally expensive algorithms in the case of large databases. Here we present an iterative method to compute a better initialization for the template estimation method proposed in [1]. The method provides ...

Cardiac disease is often associated with remodeling. Ventricular shape and function is influenced by this remodeling. Assessing left ventricular shape and motion at the population level requires establishing anatomical correspondence using registration based techniques. Cardiac magnetic resonance imaging (MRI) provides detailed quantitative data about cardiac function and geometry. Cardiac MRI ...

We propose a method to predict the subject-specific longitudinal progression of brain structures extracted from baseline MRI, and evaluate its performance on Alzheimer’s disease data. The disease progression is modeled as a trajectory on a group of di↵eomorphisms in the context of large deformation di↵eomorphic metric mapping (LDDMM). We first exhibit the limited predictive abilities of geodesi...

AT&T recently accepted an offer to be acquired by another company. So did MCI, which is what is left of MCI Worldcom. Both will become part of large local telephone companies, SBC and Verizon. Qwest also would like to buy MCI, but MCI had rejected its bid, as of this writing. Mergers sometimes result from an acquirer’s quest to fulfill a strategic vision for the future, and other times from the...

This paper presents a complete derivation and implementation of the Arbitrary Lagrangian Eulerian (ALE) formulation for the simulation of nonlinear static and dynamic problems in solid mechanics. While most of the previous work done on ALE for dynamic applications was mainly based on operator split and explicit calculations, this work derives the quasi-static and dynamic ALE equations in its si...

Lagrangian particle formulations of the large deformation diffeomorphic metric mapping algorithm (LDDMM) only allow for the study of a single shape. In this paper, we introduce and discuss both a theoretical and practical setting for the simultaneous study of multiple shapes that are either stitched to one another or slide along a submanifold. The method is described within the optimal control ...

In this paper, we propose a new algorithm to estimate diffeomorphic organ atlases out of 3D medical images. More precisely, we explore the feasibility of Kärcher means by using large deformations by diffeomorphisms (LDDMM). This framework preserves organs topology and has interesting properties to quantitatively describe their anatomical variability. We also use a new registration algorithm bas...

Abstract. In this paper we integrate semi-local patches and the weighted graph Laplacian [17] into the framework of the low dimensional manifold model [12]. This approach is much faster than the original LDMM algorithm. The number of iterations is typically reduced from 100 to 10 and the equations in each step are much easier to solve. This new approach is tested in image inpainting and denoisi...