Abstract— Common MRI sampling patterns in kspace, such as spiral trajectories, have nonuniform density and do not lie on a rectangular grid. We propose mapping the sampled data t...
This paper investigates new ways of inferring nonlinear dependence from measured data. The existence of unique linear and nonlinear sub-spaces which are structural invariants of g...
Douglas J. Leith, William E. Leithead, Roderick Mu...
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
A similarity measure is described that does not require the prior specification of features or the need for training sets of representative data. Instead large numbers of feature...
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...