A 3-D spatio-temporal deconvolution approach for MR perfusion in the brain

We propose an original spatio-temporal deconvolution approach for perfusion-weighted MRI applied to cerebral ischemia. The regularization of the underlying inverse problem is achieved with spatio-temporal priors and the resulting optimization problem is solved by half-quadratic minimization. Our approach offers strong convergence guarantees, including when the spatial priors are non-convex. Moreover, experiments on synthetic data and on real data collected from subjects with ischemic stroke show significant performance improvements over the standard approaches namely, temporal deconvolution based on either truncated singular-value decomposition or l(2)-regularization in terms of various performance measures. (C) 2013 Elsevier B.V. All rights reserved.