Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
This article presents a method aiming at quantifying the visual similarity between an image and a class model. This kind of problem is recurrent in many applications such as objec...
A mainstay in cancer diagnostics is the classification or grading of cell nuclei based on their appearance. While the analysis of cytological samples has been automated successful...
Eric Cosatto, Matthew Miller, Hans Peter Graf, Joh...
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
In relevance feedback, active learning is often used to alleviate the burden of labeling by selecting only the most informative data. Traditional data selection strategies often c...