Abstract. We propose a method to create a dual tensor atlas from multiple coregistered non-HARDI datasets. Increased angular resolution is ensured by random variations of subject p...
Matthan Caan, Caroline Sage, Maaike van der Graa...
In this paper we propose a novel parameterized macromodeling technique for analog circuits. Unlike traditional macromodels that are only extracted for a small variation space, our...
Abstract. This paper presents a novel approach for multi-organ (musculoskeletal system) automatic registration and segmentation from clinical MRI datasets, based on discrete deform...
Benjamin Gilles, Laurent Moccozet, Nadia Magnenat-...
In this paper, we study Markov Random Fields as spatial smoothing priors in fMRI detection. Relatively high noise in fMRI images presents a serious challenge for the detection algo...
Abstract. A hierarchical model based on the Multivariate Autoregessive (MAR) process is proposed to jointly model neurological time-series collected from multiple subjects, and to ...