We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coef?cients of an arbitrary li...
Karen O. Egiazarian, Alessandro Foi, Vladimir Katk...
We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
The 3-D reconstruction of cardiac vasculature using C-arm CT is an active and challenging field of research. In interventional environments patients often do have arrhythmic heart ...
Is the real problem in resolving correspondence using current stereo algorithms the lack of the "right" matching criterion? In studying the related task of reconstructin...
A novel approach to the X-ray tomography problem with sparse projection data is proposed. Non-negativity of the X-ray attenuation coefficient is enforced by modelling it as max{(x)...