Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation app...
Michael Wels, Gustavo Carneiro, Alexander Aplas,...
In this work, we are interested in technologies that will allow users to actively browse and navigate large image databases and to retrieve images through interactive fast browsin...
Background: This paper addresses the problem of recognising DNA cis-regulatory modules which are located far from genes. Experimental procedures for this are slow and costly, and ...
Irina I. Abnizova, Rene te Boekhorst, Klaudia Walt...