We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Recent works in object recognition often use visual words, i.e. vector quantized local descriptors extracted from the images. In this paper we present a novel method to build such ...
Nonlinear image registration is a prerequisite for various medical image analysis applications. Many data acquisition protocols suffer from problems due to breathing motion which h...
Martin Urschler, Joachim Bauer, Hendrik Ditt, Hors...
Abstract. This paper presents a tract-oriented analysis of diffusion tensor (DT) images of the human brain. We demonstrate that unlike the commonly used ROI-based methods for popul...
Mahnaz Maddah, Marek Kubicki, William M. Wells I...
The traditional SPM approach based on bag-of-features (BoF) must use nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effec...