Imaging in StrokeNet: Realizing the Potential of Big Data

David S Liebeskind¹, Gregory W Albers², Karen Crawford²+14

• ¹From the Neurovascular Imaging Research Core (D.S.L.) and Department of Neurology, Comprehensive Stroke Center, Geffen School of Medicine (D.S.L., J.L.S.), University of California, Los Angeles; Departments of Neurology (G.W.A.) and Radiology (M.W.), Stanford University, Palo Alto, CA; Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles (K.C., A.W.T.); Departments of Neurology and Neurological Surgery, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO (C.P.D.); Departments of Psychiatry, Radiology, and Neuroscience (M.S.G.) and Public Health Sciences (Y.Y.P., W.Z.), Medical University of South Carolina, Charleston; Ralph H Johnson VA Medical Center, Charleston, SC (M.S.G.); University of Texas Southwestern Medical Center, Austin (S.W.); Department of Neurology, Mayo Clinic, Jacksonville, FL (T.G.B.); Departments of Neurology, Public Health Sciences, Human Genetics, and Neurosurgery, Miller School of Medicine, University of Miami, FL (R.L.S.); Department of Neurology, University of Cincinnati, OH (P.K., J.P.B.); Department of Neurology, University of California, Irvine (S.C.C.); and Department of Rehabilitation Medicine, Emory University School of Medicine and Center for Visual and Cognitive Neurorehabilitation, Atlanta VA Medical Center, GA (S.L.W.). davidliebeskind@yahoo.com.+1