We describe an effective and novel approach to infer sign and direction of principal curvatures at each input site from noisy 3D data. Unlike most previous approaches, no local su...
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
We present an adaptive parametrization scheme for dynamic mesh refinement in the application of parametric image registration. The scheme is based on a refinement measure ensuring...
Michael Sass Hansen, Rasmus Larsen, Ben Glocker, N...
We introduce a method for estimating regional connectivity in diffusion tensor magnetic resonance imaging (DT-MRI) based on a fluid mechanics model. We customize the Navier-Stokes...
Nathan S. Hageman, David W. Shattuck, Katherine Na...
Computations on tensors have become common with the use of DT-MRI. But the classical Euclidean framework has many defects, and affine-invariant Riemannian metrics have been propose...
Vincent Arsigny, Pierre Fillard, Xavier Pennec, Ni...