no code implementations • 13 Dec 2018 • Line Kühnel, Alexis Arnaudon, Tom Fletcher, Stefan Sommer
We apply a stochastic generalisation of the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework to model differences in the evolution of anatomical objects detected in populations of image data.
3 code implementations • 22 Dec 2017 • Line Kühnel, Alexis Arnaudon, Stefan Sommer
In this paper, we demonstrate how deterministic and stochastic dynamics on manifolds, as well as differential geometric constructions can be implemented concisely and efficiently using modern computational frameworks that mix symbolic expressions with efficient numerical computations.
Computational Geometry Computation 53A35, 53C17, 53C44, 70H05, 22E30 G.3; G.4; G.1.4
3 code implementations • 15 Jun 2017 • Line Kühnel, Stefan Sommer
To model deformation of anatomical shapes, non-linear statistics are required to take into account the non-linear structure of the data space.
Other Computer Science 53A35
no code implementations • 1 May 2017 • Akshay Pai, Stefan Sommer, Lars Lau Raket, Line Kühnel, Sune Darkner, Lauge Sørensen, Mads Nielsen
Template estimation plays a crucial role in computational anatomy since it provides reference frames for performing statistical analysis of the underlying anatomical population variability.
no code implementations • 18 Apr 2016 • Line Kühnel, Stefan Sommer, Akshay Pai, Lars Lau Raket
This paper introduces a class of mixed-effects models for joint modeling of spatially correlated intensity variation and warping variation in 2D images.