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A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
Published on: May 20, 2016
Rob Baxter1, Thomas Nind1, James Sutherland1
1From the EPCC, University of Edinburgh, Edinburgh, Scotland, United Kingdom (R.B., A.H., R.M., D.S., A.B., B.P., W.K., D.S.M., J.F.R.H., M.P.); Health Informatics Centre (T.N., J.S., G.M., D.H., S.K., L.T., R.T., K.G., P.S.R., S.R., E.M.B., R.M., E.J.), Division of Imaging Science and Technology (D.S.), Division of Population Health and Genomics (A.D.), and Department of Computing (E.T.), University of Dundee, Dundee DD1 4HN, Scotland; Public Health Scotland, Edinburgh, Scotland (J.C., I.B., C.M., R.W.); University of Edinburgh Brain Research Imaging Centre, Edinburgh Imaging, Queen's Medical Research Institute, Edinburgh, Scotland (E.J.R.v.B.); Health Data Research UK, London, England (A.M., E.J.).
This study reviews various medical imaging techniques, including MRI, CT, and mammography, highlighting their applications and advancements. It provides insights into the evolving landscape of diagnostic imaging sequences.
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