A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the ob...
Both compressed sensing (CS) and parallel imaging effectively reconstruct magnetic resonance images from undersampled data. Combining both methods enables imaging with greater und...
Daniel S. Weller, Jonathan R. Polimeni, Leo Grady,...
Reduced rank regression (RRR) has found application in various fields of signal processing. In this paper we propose a novel extension of the RRR model which we call sparse varia...
The emerging functional MRI (Magnetic Resonance Imaging), fMRI, imaging modality was developed to obtain non-invasive information regarding the neural processes behind pre-determi...
This paper considers the problem of joint blind source separation (J-BSS), which appears in many practical problems such as blind deconvolution or functional magnetic resonance im...